ORIGINAL ARTICLE
Examining the Relationship Between Productivity Loss Trajectories and Work Disability Outcomes Using the Panel Study of Income Dynamics Elyssa Besen, PhD and Glenn Pransky, MD
Objective: To identify trajectories of productivity loss and examine the relationship between the trajectories and work disability outcomes. Methods: Latent class growth analysis of productivity loss was estimated for the ages of 25 to 44 years in the Panel Study of Income Dynamics (N = 4960). Differences among the trajectories for work disability outcomes for the ages of 25 to 64 years were estimated using logistic regression and analysis of variance. Results: A five-group trajectory model was identified with a no-risk, low-risk, high-risk, early-onset increasing risk, and late-onset increasing risk group. The likelihood of ever experiencing permanent disability or receiving Social Security Disability Insurance between the ages of 25 and 64 years differed across the trajectories with the early-onset and high-risk groups having the greatest likelihood and the no-risk trajectory having the lowest likelihood of work disability. Conclusions: Productivity loss trajectories are highly related to work disability outcomes.
P
roductivity loss for health-related reasons presents a serious economic burden for employers.1–3 Productivity loss generally encompasses three types of loss. The first type of loss is absence from work, which is often referred to as absenteeism.4–6 The second type of loss is work limitation while at work, known as presenteeism.4–6 The third type of loss is complete inability to be employed.4,5 In one company’s US workforce, chronic health conditions were estimated to cost more than $100 million per year in lost productivity.7 Another study found that on a yearly basis, employees missed an average of 2 days of work due to health-related reasons and an additional 9 days while at work were limited because of health-related reasons.8 In the United States, the annual cost for productivity loss has been found to range from $226 billion to $260 billion.9,10 A great deal of research has examined the relationship between specific chronic health conditions, such as arthritis, hypertension, and depression, and productivity loss.1,2,11,12 Research has also considered the role of health-related factors such as smoking and sleep patterns on productivity loss.13–16 Although this research sheds an important light on the impact of health on worker productivity, the majority of this research has focused on productivity loss on a one-time or limited basis, usually through a single questionnaire or single follow-up measure, providing little information on how productivity loss develops across one’s working career. There have been relatively few sources of data assessing longitudinal patFrom the Liberty Mutual Research Institute for Safety, Center for Disability Research, Hopkinton, Mass. We have no conflicts to disclose. This work was funded by the Liberty Mutual Research Institute for Safety. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.joem.org). Address correspondence to: Elyssa Besen, PhD, Liberty Mutual Research Institute for Safety, Center for Disability Research, 71 Frankland Rd, Hopkinton, MA 0178 ([email protected]). C 2015 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000493
JOEM r Volume 57, Number 8, August 2015
terns of productivity loss. One exception is a recent study examining temporal patterns of health-related productivity loss in the National Longitudinal Survey of Youth 1979 (NLSY79).17 Besen and Pransky17 identified five unique trajectories of health-related productivity loss from the ages of 25 to 44 years, using the NLSY79. In this previous study, health-related productivity loss was assessed with three items about limitations in the amount or kind of work a person could do as a result of health or being completely unable to work as a result of health. An illustration of the trajectories from this study is presented in Supplemental Digital Content Figure 1 (available at: http://links.lww.com/JOM/A208). The first trajectory the authors found was a no-risk trajectory. In the no-risk trajectory, the probability of experiencing productivity loss was close to zero across the age range representing the majority of prime working years (75.3% of the sample). The second trajectory was the low-risk trajectory. This trajectory had a relatively low probability of productivity loss. In this trajectory, there was a slight increase in the probability of productivity loss until around age 32 years and then a slight decrease after that (11.5% of the sample). The third trajectory was the late-onset increasing risk group. For this trajectory, the probability of productivity loss was initially low. Nevertheless, the probability of productivity began quickly increasing after the age of 35 years (5.5% of the sample). The fourth trajectory was the early-onset increasing risk group. Like the lateonset increasing risk group, the early-onset trajectory also had an initially low probability of productivity loss. But, for this group, the probability of productivity loss began quickly increasing around the age of 30 years (3.7% of the sample). Finally, the authors found a high risk trajectory. In this trajectory, there was an initial increase in the probability of productivity loss from ages 25 to 30 years after which the probability remained relatively high (4.0% of the sample)17 . Important differences between the trajectories were found with regard to experiencing chronic health conditions and general health status by the age of 40 years, employment outcomes at midlife (approximately ages 45 to 46 years), and personal and demographic characteristics, including education, mastery, self-esteem, and socioeconomic status. The high-risk and early-onset trajectories had the greatest number of chronic health conditions, followed by the late-onset trajectory, and the low-risk trajectory. The no-risk trajectory had the fewest chronic health conditions.18 A similar pattern was reported for general physical and mental health with the high-risk, early-onset, and late-onset trajectories having the lowest levels of physical and mental health, followed by the low-risk trajectory, and then the no-risk trajectory.17 For employment outcomes at midlife, more than 90% of individuals in the no-risk and low-risk trajectories worked 10 weeks or more in the previous year, whereas in the other three trajectories only about half of individuals reported working in midlife. Last, for education, mastery, self-esteem, and socioeconomic status, the no-risk trajectory had the highest levels of these characteristics whereas the high-risk and early-onset trajectories had the lowest levels.17 The study by Besen and Pransky17 had important findings relating to the longitudinal patterns of experiencing productivity loss across one’s working career, but their findings were limited to a 829
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single cohort who were aged 14 to 22 years in 1979, which raises questions about whether these trajectories are able to be replicated or if they are specific to that particular cohort from that one study. In addition, the NLSY79 did not measure the work disability outcomes of being permanently disabled or receiving Social Security Disability Insurance (SSDI), which are important indicators of likely permanent departure from the workforce. The goal of this study is to evaluate these trajectories in a unique data set that represents multiple birth cohorts and has specific information on outcomes representing significant work disability. If similar trajectories emerge, this will speak to the robustness of how these patterns of productivity loss develop over time and will have implications for the use of the trajectories in research and practice. In addition, the inclusion of specific work disability outcomes will allow for a better understanding of differences across the trajectories in premature work withdrawal and the contribution of each trajectory toward the number of persons receiving permanent disability (PD) benefits from public programs.
METHODS Participants This study utilized data from the Panel Study of Income Dynamics (PSID).19 The PSID is a nationally representative longitudinal study of US households that gathers information on employment, income, health, and family demographics. A key informant, usually the head of the household, provides information about the entire family, including his or her spouse when present. The study started in 1968 with approximately 5000 households, representing more than 18,000 individuals. It has grown to about 9000 households and more than 24,000 individuals in the 2011 survey, which is the most recent survey year publically available. The sample of households in the PSID has continued to grow as children of the original households get married, have their own children, and form new, separate households that are added to the sample. Households have been surveyed annually until 1997 and then every other year after that point. In this study, we limit our sample to individuals who participated in at least six waves of the PSID from the ages of 25 to 44 years and who had valid responses on the questions used in the trajectory model, that are described in the next section. Because the PSID involves participants entering the study at various ages, the survey years representing ages 25 to 44 years were different across participants. The data were restructured so that each wave corresponds to an age instead of a survey year, similar to other previous research.17,20,21 We further restricted the sample to individuals who participated in the surveys at the ages of 25 or 26 years and again at the ages of 43 or 44 years, which roughly reflects the ages in the first and last waves used in the prior trajectory model, yielding a sample of 4960 unique cases. Included in our sample are heads of households and partners of the heads. These data restrictions roughly reflect those used in the previous study by Besen and Pransky, which identified productivity loss trajectories in the NLSY79.17
Measures Productivity Loss In each survey, the heads of households were asked whether they had a physical or nervous condition that limits the type of work or the amount of work they can do. This question was asked of all heads of households starting in 1968, and then of all spouses in 1978 and from 1981 onwards. Responses were coded 1 for yes and 0 for no. Productivity loss was asked as a single question in 1968 and from 1972 onwards; however, from 1969 to 1971, participants were asked, “Do you have any physical or nervous condition that limits the kind of work you can do?” and “Do you have any physical or nervous condition that limits the amount of work you can do?” We combined these items and coded individuals as yes if they responded “yes” to either question and no if they responded “no” to both questions. 830
Trajectory Baseline Covariates The trajectory model was adjusted for sex, race, and education. Sex was coded 1 for female and 0 for male. Race was coded 1 for white and 0 for nonwhite. Education was coded as a continuous variable, indicating the maximum number of years of education observed across waves that an individual participated in the PSID.
Work Disability Outcomes We assessed work disability, using three methods. First, starting in 1976, when heads of households were asked about their work status with the question “We would like to know about what you do-–are you working now, looking for work, retired, a student, a housewife, or what?”, one of the response options was “permanently disabled.” Prior to 1976, “permanently disabled” was not treated as an independent response option, and so for this study, we use only responses from 1976 onwards. In 1979, “permanently disabled” was included as a response option in reference to spouse’s work status as well. Responses were coded as 1 for permanently disabled or 0 for any other option. The other options included “working now,” “only temporarily laid off,” “looking for work, unemployed,” “retired,” “housewife,” “student,” and “other.” We refer to this measure as PD. The second method for evaluating work disability was based on receiving social security. Starting in 1986, a separate question was used for heads of households and spouses about receiving social security income. If individuals report receiving social security, they are asked a follow-up question about the type of social security, with a response option of “disability.” Responses were coded 1 for receiving SSDI and 0 for not receiving SSDI. We refer to this measure as SSDI. As a final method for assessing work disability, we combined the responses from the first two work disability items. Individuals’ responses were coded as 1 if an individual responded that he or she was permanently disabled and/or was receiving SSDI and 0 if an individual did not respond affirmatively to either question. Because the social security disability question was not assessed until 1986, from 1976 to 1985, the responses for this method of assessing work disability were identical to the responses to the work status question. We refer to this measure as any long-term disability (ALTD).
Analytic Strategy We conducted our analyses in two stages. In the first stage, we estimated the trajectory model, using the user-written program “traj” for STATA, which is used for latent class growth analysis.22 Latent class growth analysis is a type of growth mixture modeling where distinct subgroups of individuals after similar development trajectories are identified.23 In this type of analysis, the number of trajectories, as well as the shape of the trajectories, is prespecified. Because our trajectory analysis was aimed at replicating previous findings, we used the same specifications as in the study by Besen and Pransky.17 This involved estimating a five-group trajectory model using the logit option to evaluate the probability of productivity loss where all trajectories had a quadratic shape. The model was assessed over the age range 25 to 44 years, as this roughly corresponded to the age range in the prior trajectory analysis and represents the majority of prime working years. In the trajectory analysis, a new variable was generated that grouped individuals into the different trajectories based on the maximum likelihood probability rule.24,25 This grouping variable was then used in subsequent analyses. In the second stage of the analyses, we focused on differences in the work disability outcomes across the productivity loss trajectories. We examined the work disability outcomes for two separate age ranges, first within the trajectory age range of 25 to 44 years, and then after the trajectory period, by examining ages 45 to 64 years. Within each given age, there was a significant number of missing values as the survey switched from annual to biennial in 1997, the
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Relationship Between Productivity Loss Trajectories and Work Disability Outcomes
questions relating to work disability were not asked in every survey, and in many cases individuals did not participate in every survey, either because of study attrition or in the case of the analyses for the age range after the trajectory period, some individuals had not yet reached those ages. To include as many individuals as possible in the second stage of analyses, we created aggregate measures of work disability, which combined responses to the disability questions for the two age ranges (25 to 44 years and 45 to 64 years), respectively. For PD, if individuals ever reported being permanently disabled from the ages of 25 to 44 years, they were coded as a 1. If individuals never reported being permanently disabled during those ages, they were coded as 0. An aggregate work disability measure was also created for the trajectory follow-up age range of 45 to 64 years using the same coding strategy. An identical coding strategy was used for individuals receiving SSDI and for the ALTD measure. To evaluate the prevalence of work disability in the two age ranges, we also created variables for the three work disability outcomes (PD, SSDI, and ALTD) that represented the percentage of waves within the two age ranges where individuals responded to the work disability questions and had affirmative responses. A separate prevalence
variable was created for each of the work disability outcomes for the two age ranges. In cases where individuals did not respond to a work disability question within a given age range, those individuals were excluded from the second stage of analyses. Supplemental Digital Content Tables 1 (available at: http://links.lww.com/JOM/A206) and 2 (available at: http://links.lww.com/JOM/A207) provide information on the number of waves that individuals responded to the work disability questions for the two age ranges. Logistic regression models were used to examine the relationships between membership in the different trajectory groups and the odds of ever reporting being permanently disabled and/or receiving SSDI benefits. Separate models were estimated for ages 25 to 44 years and ages 45 to 64 years, as well as for the three work disability outcomes. These models were adjusted for sex, race, and education. To examine differences in the prevalence of work disability across the trajectory groups, analysis of covariance was used. We used separate models for each of the work disability outcomes and for each of the two age ranges. The covariates included were sex, race, and education. All analyses were conducted using STATA 13.1 (StataCorp LP, College Station, TX).
TABLE 1. Logistic Regression Model for Work Disability Outcomes From the Ages of 25 to 44 Yearsa Permanent Disability, (N = 4960) OR Low risk (LR) Late onset (LO) Early onset (EO) High risk (HR) Female White Education Intercept
Social Security Disability Income, (N = 4960) 95% CI
OR
Any Long-Term Disability, (N = 4960) 95% CI
OR
95% CI
12.79*** 8.40–19.47 3.94*** 2.07–7.50 9.20*** 6.38–13.26 28.31*** 19.36–41.40 10.81*** 6.64–17.59 18.40*** 13.25–25.56 95.33*** 62.77–144.78 45.70*** 28.68–72.82 62.26*** 42.86–90.44 89.22*** 55.12–144.42 42.49*** 24.74–72.99 57.99*** 37.14–90.55 1.42** 1.09–1.84 0.79 0.56–1.11 1.19 0.93–1.51 0.35*** 0.27–0.45 0.46*** 0.33–0.64 0.33*** 0.26–0.42 0.82*** 0.77–0.87 0.91* 0.84–0.99 0.83*** 0.78–0.88 0.02*** 0.01–0.02 0.01*** 0.01–0.02 0.03*** 0.02–0.04 Wald Test Comparisonsb Wald Test Comparisonsb Wald Test Comparisonsb EO, HR > LO, LR; LO > LR EO, HR > LO, LR; LO > LR EO, HR > LO, LR; LO > LR
*P < 0.05; ** P < 0.01; ***P < 0.001. a The no-risk trajectory is the reference group for the models. b All comparisons are based on Wald tests significant at P < .05. CI, confidence interval; OR, odds ratio.
TABLE 2. Prevalence of Experiencing Work Disability Outcomes From the Ages of 25 to 44 Years Prevalence
Disability Outcome
No Risk (NR) (n = 3763)
Low Risk (LR) (n = 412)
Late Onset (LO) (n = 432)
Early Onset (EO) (n = 225)
High Risk (HR) (n = 128)
F Test
Permanent Disability
0.4%
2.0%
3.3%
12.3%
18.2%
462.43***
Social Security Disability Income
0.3%
1.0%
1.9%
10.3%
12.4%
190.41***
Any Long-Term Disability
0.5%
2.5%
3.7%
14.3%
21.5%
498.67***
Pairwise Comparisona HR > EO, LO, LR, NR; EO > LO, LR, NR; LO > LR, NR; LR > NR HR > EO, LO, LR, NR; EO > LO, LR, NR; LO, LR > NR HR > EO, LO, LR, NR; EO > LO, LR, NR; LO > LR, NR; LR > NR
***P < 0.001. a All comparisons are based on significance at P < .05. EO, early onset; HR, high risk; LO, late onset; LR, low risk; NR, no risk.
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RESULTS
initially had a slight increase in the probability of productivity loss from ages 25 to 30 years and then remained relatively high thereafter.
Descriptives In the trajectory sample, 43% of the sample was female and 67% were white. The large majority of the sample (83%) had 12 or more years of education. Within the trajectory age range of 25 to 44 years, the number of waves individuals participated in ranged from 6 to 20, with less than 3% of the sample participating in fewer than 10 waves. The survey year in which participants first entered the trajectory age range went from 1968 until 1993. For the trajectory follow-up age range of 45 to 64 years, the number of waves individuals participated in ranged from 0 to 15 waves, with about half of the sample (51%) completing fewer than five waves.
Productivity Loss Trajectories A five-group trajectory model was found to fit the data. The trajectories were roughly the same as those identified by Besen and Pransky,17 using the NLSY79, and in the presentation of the current trajectory model, we have applied the same labels as previously used. The trajectories are plotted in Fig. 1. The trajectories from the previous study are presented in Supplemental Digital Content Figure 1 (available at: http://links.lww.com/JOM/A208). A posterior probability of 0.80 per a trajectory group for those assigned to that respective trajectory indicates a good model fit.26 The mean posterior probability per trajectory ranged from 0.84 to 0.97. In addition, the mean posterior probability for individuals not assigned to the given trajectory was less than 0.10, further showing a good model fit. The no-risk trajectory characterized three quarters of the sample (75.9%) and showed a stable zero probability of productivity loss over time. The low-risk trajectory accounted for 8.3% of the sample and had a relatively low probability of productivity loss over time, with a slight increase in the probability up to the age of 32 years and then a slight but steady decrease after that point. The late-onset increasing risk trajectory characterized 8.7% of the sample, showing an initially low probability of productivity loss, which began quickly increasing around the age of 35 years. We also identified an earlyonset increasing risk trajectory that had an initially low probability of productivity loss followed by a steadily increasing probability beginning around the age of 40 years and then leveling off after that point. This trajectory accounted for 4.5% of the sample. The final group was a high-risk trajectory representing 2.6% of the sample, which
Disability Outcomes for Ages 25 to 44 Years (Trajectory Age Range) Using the trajectory grouping variable identified in the trajectory model, we examined differences in the odds of experiencing different disability outcomes across the trajectory groups for the age range within the trajectory period of 25 to 44 years. The results of the logistic regression models for the 25- to 44-year age range are presented in Table 1. The no-risk group was used as the reference group for analyses. We also conducted Wald tests with one degree of freedom to compare the nonreference trajectory groups in the logistic regression models. Across the disability outcomes (PD, SSDI, and ALTD), a similar pattern was observed where the odds of ever experiencing the specific type of disability within the ages 25 to 44 years were highest for the high-risk and early-onset trajectories, followed by the late-onset trajectory and then the lowrisk trajectory. The odds of experiencing the different work disability outcomes were between 42 and 89 times higher for the highrisk trajectory, 46 to 95 times higher for the early-onset trajectory, 11 to 28 times higher for the late -onset trajectory, and 4 to 13 times higher for the low-risk trajectory relative to the no-risk trajectory. The confidence intervals for the odds ratios were somewhat large, suggesting that the precision of the odds ratios be interpreted cautiously. To further examine differences across the trajectory groups, we assessed differences in the prevalence of experiencing the work disability outcomes within the waves of the study in which individuals participated between the ages of 25 and 44 years. As shown in Table 2, across all three work disability measures, we found the high-risk trajectory to have a greater prevalence of waves experiencing work disability than all other trajectories, ranging from a high of 21.5% of the waves for having ALTD and a low of 12.4% for receiving SSDI. The early-onset risk trajectory was also found to have a greater prevalence for the three work disability outcomes relative to the late-onset, low-risk, and no-risk trajectories, ranging from 10% of the waves to 14% of the waves. Both the no-risk and low-risk trajectories had a relatively low prevalence of waves with work disability across the three types, with prevalence between 1% and 3% for the low-risk trajectory and less than 1% for the no-risk trajectory.
Disability Outcomes for Ages 45 to 64 Years (Trajectory Follow-Up Age Range)
FIGURE 1. Trajectories of the probability of productivity loss across the ages of 25 to 44 years in the Panel Study of Income Dynamics. 832
We replicated the analyses presented earlier for the age range after the trajectory period, specifically for the ages 45 to 64 years. The results of the logistic regression models are presented in Table 3. The odds of experiencing the different disability outcomes (PD, SSDI, and ALTD) in the follow-up age range were much smaller than those for the odds within the trajectory age range; however, several differences still emerged. Relative to the no-risk trajectory, the odds of experiencing the different disability outcomes were highest for the early-onset trajectory ranging from 11 to 14 times higher, followed by the high-risk trajectory ranging from 7 to 10 times higher, and the late-onset trajectory ranging from 6 to 7 times higher. The odds for the low-risk trajectory were around two times higher than those for the no-risk trajectory. The results for the analyses of the prevalence of waves experiencing work disability for the age range 45 to 64 years are presented in Table 4. We found that in roughly a third of the waves in which individuals participated, that individuals in the high-risk and early-onset trajectories experienced some type of work disability. For receiving SSDI specifically, the prevalence was a bit lower at about a fifth of the waves for the high-risk and early-onset trajectories. The prevalence of experiencing work disability for the late-onset trajectory C 2015 American College of Occupational and Environmental Medicine
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Relationship Between Productivity Loss Trajectories and Work Disability Outcomes
TABLE 3. Logistic Regression Model for Work Disability Outcomes From the Ages of 45 to 64 Yearsa Social Security Disability Income, (n = 4293)
Permanent Disability, (n = 4293)
Low risk (LR) Late onset (LO) Early onset (EO) High risk (HR) Female White Education Intercept
Any Long-Term Disability, (n = 4293)
OR
95% CI
OR
95% CI
OR
95% CI
2.26*** 6.75*** 13.92*** 9.83*** 1.34** 0.40*** 0.79*** 0.08*** Wald Test Comparisonsb EO > LO, LR; HR, LO > LR
1.58–3.23 5.08–8.97 9.88–19.62 6.31–15.33 1.07–1.67 0.32–0.50 0.75–0.84 0.06–0.10
1.67* 6.14*** 10.82*** 6.98*** 1.31* 0.56*** 0.81*** 0.05*** Wald Test Comparisonsb EO > LO, LR; HR, LO > LR
1.09–2.56 4.55–8.30 7.61–15.41 4.36–11.19 1.03–1.67 0.44–0.71 0.77–0.86 0.04–0.07
1.94*** 7.29*** 13.28*** 10.25*** 1.38** 0.41*** 0.80*** 0.09*** Wald Test Comparisonsb EO > LO, LR; HR, LO > LR
1.37–2.74 5.58–9.53 9.50–18.56 6.66–15.76 1.12–1.70 0.33–0.51 0.76–0.84 0.08–0.11
*P < 0.05; ** P < 0.01; ***P < 0.001. a The no-risk trajectory is the reference group for the models. b All comparisons are based on Wald tests significant at P < .05. CI, confidence interval; OR, odds ratio.
TABLE 4. Prevalence of Experiencing Work Disability Outcomes From the Ages of 45 to 64 Years Prevalence No Risk (NR) (n = 3261)
Low Risk (LR) (n = 356)
Late Onset (LO) (n = 377)
Early Onset (EO) (n = 191)
High Risk (HR) (n = 108)
F Test
Pairwise Comparisona
Permanent Disability (PD)
2.9%
5.4%
16.8%
30.5%
24.1%
200.05***
Social Security Disability Income (SSDI) Any Long-Term Disability (ALTD)
2.0%
3.4%
12.3%
23.9%
20.8%
160.92***
3.7%
6.6%
21.7%
36.7%
32.6%
250.62***
EO > HR, LO, LR, NR; HR > LO, LR, NR; LO > LR, NR; LR > NR EO, HR > LO, LR, NR; LO > LR, NR EO, HR > LO, LR, NR; LO > LR, NR; LR > NR
Disability Outcome
*P < 0.05; ** P < 0.01; ***P < 0.001. a All comparisons are based on significance at P < .05.
ranged between 12% and 22% of the waves in which individuals participated across the different types of work disability. The prevalence was somewhat lower for the no-risk and low-risk trajectories, ranging from 3% to 7% for the low-risk trajectory and ranging from 2% to 4% for the no-risk trajectory.
DISCUSSION This study evaluated longitudinal trajectories of the probability of experiencing health-related productivity loss from the ages of 25 to 44 years using the PSID. Understanding the various pathways of changing productivity loss and disability status over time may help provide a longer-term perspective on disability issues and when to best target and provide disability prevention strategies. Using the trajectories identified with the PSID, we examined differences across the trajectories in work disability outcomes for the age range within the trajectory period of 25 to 44 years, as well as the age range after the trajectory period from the ages 45 to 64 years. Several interesting findings emerged. In line with a previous study that identified five trajectories of health-related productivity loss using the NLSY79,17 we also found a five-group trajectory model with remarkably similar patterns when
using the PSID. In this trajectory model, there was a no-risk trajectory that had a constant zero probability of productivity loss, a low-risk trajectory that also had a relatively low probability of productivity loss, although it was slightly higher than that in the no-risk trajectory, two increasing risk trajectories, and a high-risk trajectory that had a mostly stable high probability of productivity loss across the ages of 25 to 44 years. The first increasing risk trajectory was the earlyonset trajectory that started with a low probability of productivity loss but the probability began quickly increasing around the age of 30 years. The late-onset increasing risk trajectory also started with a relatively low probability of productivity loss, but in this trajectory, the probability did not begin to quickly increase until closer to the age of 35 years. These five trajectories very closely matched those previously identified with one exception from the ages 40 to 44 years. In this study, the early-onset trajectory starts to level out at a high probability of productivity loss, but it does not actually turn and start decreasing between the ages of 40 to 44 years. In contrast, in their previous study, the authors17 found a slight turning point during those years. This difference may be negligible though as the probability of productivity loss for the early-onset trajectory in both studies remains high.
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Regarding the work disability outcomes, within the ages of 25 to 44 years, the productivity loss trajectories were found to be highly related to differences in work disability outcomes. In terms of receiving SSDI, the low-risk, late-onset, early-onset, and high-risk trajectories were all more likely to have received SSDI one or more times from the ages of 25 to 44 years. The early-onset and high-risk trajectories were also more likely to have received SSDI than either the low-risk or late-onset trajectories. Both the early-onset and highrisk trajectories received SSDI in more than 10% of the waves they participated in from the ages of 25 to 44 years, whereas the other three trajectories received SSDI in less than 2% of waves. In terms of reporting being permanently disabled, a similar pattern emerged, with the high-risk group reporting being permanently disabled in close to 20% of the waves from the ages of 25 to 44 years, and the early-onset group reporting PD in more than 10% of the waves. In contrast, the no-risk group reported PD in less than 1% of waves. Membership in the different trajectories was also found to be highly related to differences in the work disability outcomes from the ages of 45 to 64 years. Relative to the no-risk trajectory, the other four trajectories all had a greater likelihood of receiving SSDI or being permanently disabled in at least 1 year between the ages of 45 to 64 years. The early-onset trajectory also had a greater likelihood of receiving SSDI or being permanently disabled in at least 1 year than the late-onset and low-risk trajectories. In addition, both the high-risk and late-onset trajectories had a greater likelihood of receiving SSDI or being permanently disabled in at least 1 year than that low-risk trajectory. For both the early-onset and high-risk trajectories, individuals experienced some type of long-term disability in approximately a third of the waves they participated in from the ages of 45 to 64 years. In contrast, the late-onset trajectory experienced ALTD in only about a fifth of the waves they participated in and the low-risk and no-risk trajectories experienced ALTD in less than 10% of the waves. Research has not previously examined the relationship between health-related productivity loss trajectories and work disability outcomes; however, our findings regarding differences in the likelihood of experiencing ALTD across the trajectories are in line with previous studies indicating a relationship between aspects of productivity loss and work disability outcomes. For example, studies have shown that previous sick leave, which may be considered an aspect of productivity loss in regard to absenteeism, is a strong predictor of subsequently being granted a disability pension.27–30 One study found that a considerable number of individuals with sick leave related to arthritis ultimately become permanently disabled from work.31 Other research has illustrated a relationship between work ability, which is closely linked to work limitation, and later receipt of a disability pension.32,33 Much of this research is conducted outside of the United States in countries with well-established disability pension systems such as the Netherlands and Denmark; thus, this study helps illustrate consistent findings in the US context where the disability system is somewhat different.
Implications There are several important implications of the findings of this study. First, this study illustrates that there are multiple patterns for productivity loss developing across the lifespan. As can be seen in the high-risk trajectory, for some individuals there is a constant high probability of productivity loss, which suggests that there was not a single event in adulthood, after which an individual had permanent productivity loss, rather these individuals likely have lifelong conditions that impact work ability and eventually lead to permanent withdrawal from the labor force. In contrast, for other individuals such as those in the two delayed onset trajectories, the probability of productivity loss begins quickly increasing after a certain point, in this case either age 30 or 35 years. It is possible that in these trajectories, there was a single event such as a specific diagnosis after 834
which work ability was permanently impacted. Unfortunately, in this study we do not have information on the exact cause of individuals’ productivity loss and thus we are not able to confirm whether the reasons for productivity are specific to the different trajectories, but previous research has shown that the incidence of chronic illness differs across the trajectories.18 A second implication has to do with the robustness of our findings relating to the different temporal patterns. It is rare that extensive longitudinal data covering more than a 20-year span from the ages of 25 to 44 years would exist with multiple populations and with comparable measures on productivity loss. Nevertheless, in the United States there are two nationally representative ongoing longitudinal studies that make this possible: the NLSY79 and the PSID. The trajectories identified in this study using the PSID very closely replicate the findings of a previous longitudinal study that used the NLSY79.17 As such, we believe that this study helps support both the validity and reliability of these productivity loss trajectories. A final implication relates to our findings showing differences in key work disability outcomes, including receiving SSDI. In the United States, both the number of beneficiaries in the social security disability program and the cost of benefits for recipients have been increasing over time.34 In fact, over the past decade, the cost of SSDI has doubled reaching an all-time high of $144 billion in 2014 and this is a federal program paid for by taxpayers.35 The SSDI fund is expected to be exhausted by 2016 raising concerns for policymakers. The results of this study have implications for identifying individuals early on who may be at risk of ultimately receiving SSDI. Being in either the high-risk or early-onset trajectory was strongly related to receiving SSDI at some point from the ages of 25 to 64 years. As such, these workers may be a potential group for intervention to prevent becoming permanently disabled. Future research utilizing these trajectories is needed to further identify baseline factors that differ across the trajectories that may be used for finding individuals at risk for poor work disability outcomes.
Limitations Despite our use of a large, nationally representative longitudinal data set covering approximately 5000 individuals, there are a few important limitations to acknowledge. A major limitation with the PSID is that there is no information available about what specific health conditions are responsible for the health-related productivity loss. As such, we do not know if there are differences across trajectories in what causes the productivity loss and whether the same conditions cause the productivity loss at each given age. Another limitation has to do with the measures of work disability. These measures were not asked in every wave. This resulted in the incomplete capture of information on whether individuals reported being permanently disabled or receiving SSDI. Although we found large differences across the trajectories in the work disability outcomes, the magnitude of the differences may have been biased by the lack of information on work disability at certain ages for certain trajectories. Because the questions were asked or not asked at a given age in the same manner across the trajectories, the bias would have been evenly distributed across groups. This does seem to be the case as there were similar percentages of individuals in the different trajectories having answered the work disability questions in similar frequencies. For the work disability outcomes between the ages of 45 and 64 years, several individuals had not yet reached the ages in this range. As a result, it will be important to continue to update the analyses as more waves of data become available. As with any longitudinal study, there may have been historical changes relating to the variables in the study that make comparison of the variables at different time points difficult. For example, changes in legislation concerning work disability from 1968 to 2011 may have impacted our findings. Unfortunately, in the analyses there is no way to control for this. Nevertheless, the impact of historical effects may
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have been partially mitigated as multiple cohorts were included in our sample. For example, some individuals in the sample may have turned 25 years in 1968, whereas others turned 25 years in 1979, meaning that they would have been subject to different historical influences at any given age. Future research is needed to examine the influence of changes in legislation and other policies that may influence work disability over time.
CONCLUSIONS Health-related productivity loss costs employers billions of dollars each year. As such gaining a greater understanding of how productivity loss develops over one’s working years is of significance. This study identified five unique trajectories of productivity loss using the PSID which were found to closely mirror trajectories that were previously identified using a different data source. The likelihood of receiving SSDI or being permanently disabled at some point from the ages of 25 to 64 years was found to vary greatly across the different trajectories. The trajectories from this study may be useful to future research in identifying individuals at risk of becoming permanently disabled.
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14. Boles M, Pelletier B, Lynch W. The relationship between health risks and work productivity. J Occup Environ Med. 2004;46:737–745. 15. Burton WN, Chen C-Y, Conti DJ, Schultz AB, Pransky G, Edington DW. The association of health risks with on-the-job productivity. J Occup Environ Med. 2005;47:769–777. 16. Rosekind MR, Gregory KB, Mallis MM, Brandt SL, Seal B, Lerner D. The cost of poor sleep: workplace productivity loss and associated costs. J Occup Environ Med. 2010;52:91–98. 17. Besen E, Pransky G. Trajectories of productivity loss over a 20-year period: an analysis of the National Longitudinal Survey of Youth. Scand J Work Environ Health. 2014;40:380–389. 18. Besen E, Pransky G. Assessing the relationship between chronic health conditions and productivity loss trajectories. J Occup Environ Med. 2014;56:1249– 1257. 19. Institute for Social Research. Panel Study of Income Dynamics. Ann Arbor, MI: Institute for Social Research, Survey Research Center, University of Michigan; 2015. 20. Meyer JD, Mutambudzi M. Construction of life-course occupational trajectories: evidence for work as a mediator of racial disparities in hypertension. J Occup Environ Med. 2012;54:1201–1207. 21. Østbye T, Malhotra R, Landerman LR. Body mass trajectories through adulthood: results from the National Longitudinal Survey of Youth 1979 Cohort (1981–2006). Int J Epidemiol. 2011;40:240–250. 22. Jones BL, Nagin DS. A note on a Stata plugin for estimating group-based trajectory models. Sociol Methods Res. 2013;42:608–613. 23. Jung T, Wickrama K. An introduction to latent class growth analysis and growth mixture modeling. Soc Personal Psychol Compass. 2008;2:302–317. 24. Jones BL, Nagin DS. Advances in group-based trajectory modeling and an SAS procedure for estimating them. Sociol Methods Res. 2007;35:542–571. 25. Jones BL, Nagin DS, Roeder K. A SAS procedure based on mixture models for estimating developmental trajectories. Sociol Methods Res. 2001;29:374– 393. 26. Nagin D. Group-Based Modeling of Development. Cambridge, MA: Harvard University Press; 2009. 27. Wallman T, Wedel H, Palmer E, et al. Sick-leave track record and other potential predictors of a disability pension. A population based study of 8,218 men and women followed for 16 years. BMC Public Health. 2009;9:104. 28. Lund T, Kivim¨aki M, Labriola M, Villadsen E, Christensen KB. Using administrative sickness absence data as a marker of future disability pension: the prospective DREAM study of Danish private sector employees. Occup Environ Med. 2008;65:28–31. 29. Virtanen M, Kivim¨aki M, Vahtera J, et al. Sickness absence as a risk factor for job termination, unemployment, and disability pension among temporary and permanent employees. Occup Environ Med. 2006;63:212–217. 30. Alexanderson KA, Borg KE, Hensing GK. Sickness absence with low-back, shoulder, or neck diagnoses: an 11-year follow-up regarding gender differences in sickness absence and disability pension. Work. 2005;25:115–124. 31. Zirkzee EJ, Sneep AC, de Buck PD, et al. Sick leave and work disability in patients with early arthritis. Clin Rheumatol. 2008;27:11–19. 32. Alavinia SM, De Boer A, Van Duivenbooden J, Frings-Dresen M, Burdorf A. Determinants of work ability and its predictive value for disability. Occup Med. 2009;59:32–37. 33. Liira J, Matikainen E, Leino-Arjas P, et al. Work ability of middle-aged Finnish construction workers—“a follow-up study in 1991–1995.” Int J Ind Ergon. 2000;25:477–481. 34. US Social Security Administration. Trends in the Social Security and Supplemental Security Income Disability Programs. Washington, DC: US Social Security Administration; 2015. 35. DeHaven T. The Rising Cost of Social Security Disability Insurance. Washington, DC: Cato Institute; 2013.
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Examining the Relationship Between Productivity Loss Trajectories and Work Disability Outcomes Using the Panel Study of Income Dynamics Elyssa Besen, PhD and Glenn Pransky, MD
Objective: To identify trajectories of productivity loss and examine the relationship between the trajectories and work disability outcomes. Methods: Latent class growth analysis of productivity loss was estimated for the ages of 25 to 44 years in the Panel Study of Income Dynamics (N = 4960). Differences among the trajectories for work disability outcomes for the ages of 25 to 64 years were estimated using logistic regression and analysis of variance. Results: A five-group trajectory model was identified with a no-risk, low-risk, high-risk, early-onset increasing risk, and late-onset increasing risk group. The likelihood of ever experiencing permanent disability or receiving Social Security Disability Insurance between the ages of 25 and 64 years differed across the trajectories with the early-onset and high-risk groups having the greatest likelihood and the no-risk trajectory having the lowest likelihood of work disability. Conclusions: Productivity loss trajectories are highly related to work disability outcomes.
P
roductivity loss for health-related reasons presents a serious economic burden for employers.1–3 Productivity loss generally encompasses three types of loss. The first type of loss is absence from work, which is often referred to as absenteeism.4–6 The second type of loss is work limitation while at work, known as presenteeism.4–6 The third type of loss is complete inability to be employed.4,5 In one company’s US workforce, chronic health conditions were estimated to cost more than $100 million per year in lost productivity.7 Another study found that on a yearly basis, employees missed an average of 2 days of work due to health-related reasons and an additional 9 days while at work were limited because of health-related reasons.8 In the United States, the annual cost for productivity loss has been found to range from $226 billion to $260 billion.9,10 A great deal of research has examined the relationship between specific chronic health conditions, such as arthritis, hypertension, and depression, and productivity loss.1,2,11,12 Research has also considered the role of health-related factors such as smoking and sleep patterns on productivity loss.13–16 Although this research sheds an important light on the impact of health on worker productivity, the majority of this research has focused on productivity loss on a one-time or limited basis, usually through a single questionnaire or single follow-up measure, providing little information on how productivity loss develops across one’s working career. There have been relatively few sources of data assessing longitudinal patFrom the Liberty Mutual Research Institute for Safety, Center for Disability Research, Hopkinton, Mass. We have no conflicts to disclose. This work was funded by the Liberty Mutual Research Institute for Safety. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.joem.org). Address correspondence to: Elyssa Besen, PhD, Liberty Mutual Research Institute for Safety, Center for Disability Research, 71 Frankland Rd, Hopkinton, MA 0178 ([email protected]). C 2015 by American College of Occupational and Environmental Copyright Medicine DOI: 10.1097/JOM.0000000000000493
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terns of productivity loss. One exception is a recent study examining temporal patterns of health-related productivity loss in the National Longitudinal Survey of Youth 1979 (NLSY79).17 Besen and Pransky17 identified five unique trajectories of health-related productivity loss from the ages of 25 to 44 years, using the NLSY79. In this previous study, health-related productivity loss was assessed with three items about limitations in the amount or kind of work a person could do as a result of health or being completely unable to work as a result of health. An illustration of the trajectories from this study is presented in Supplemental Digital Content Figure 1 (available at: http://links.lww.com/JOM/A208). The first trajectory the authors found was a no-risk trajectory. In the no-risk trajectory, the probability of experiencing productivity loss was close to zero across the age range representing the majority of prime working years (75.3% of the sample). The second trajectory was the low-risk trajectory. This trajectory had a relatively low probability of productivity loss. In this trajectory, there was a slight increase in the probability of productivity loss until around age 32 years and then a slight decrease after that (11.5% of the sample). The third trajectory was the late-onset increasing risk group. For this trajectory, the probability of productivity loss was initially low. Nevertheless, the probability of productivity began quickly increasing after the age of 35 years (5.5% of the sample). The fourth trajectory was the early-onset increasing risk group. Like the lateonset increasing risk group, the early-onset trajectory also had an initially low probability of productivity loss. But, for this group, the probability of productivity loss began quickly increasing around the age of 30 years (3.7% of the sample). Finally, the authors found a high risk trajectory. In this trajectory, there was an initial increase in the probability of productivity loss from ages 25 to 30 years after which the probability remained relatively high (4.0% of the sample)17 . Important differences between the trajectories were found with regard to experiencing chronic health conditions and general health status by the age of 40 years, employment outcomes at midlife (approximately ages 45 to 46 years), and personal and demographic characteristics, including education, mastery, self-esteem, and socioeconomic status. The high-risk and early-onset trajectories had the greatest number of chronic health conditions, followed by the late-onset trajectory, and the low-risk trajectory. The no-risk trajectory had the fewest chronic health conditions.18 A similar pattern was reported for general physical and mental health with the high-risk, early-onset, and late-onset trajectories having the lowest levels of physical and mental health, followed by the low-risk trajectory, and then the no-risk trajectory.17 For employment outcomes at midlife, more than 90% of individuals in the no-risk and low-risk trajectories worked 10 weeks or more in the previous year, whereas in the other three trajectories only about half of individuals reported working in midlife. Last, for education, mastery, self-esteem, and socioeconomic status, the no-risk trajectory had the highest levels of these characteristics whereas the high-risk and early-onset trajectories had the lowest levels.17 The study by Besen and Pransky17 had important findings relating to the longitudinal patterns of experiencing productivity loss across one’s working career, but their findings were limited to a 829
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single cohort who were aged 14 to 22 years in 1979, which raises questions about whether these trajectories are able to be replicated or if they are specific to that particular cohort from that one study. In addition, the NLSY79 did not measure the work disability outcomes of being permanently disabled or receiving Social Security Disability Insurance (SSDI), which are important indicators of likely permanent departure from the workforce. The goal of this study is to evaluate these trajectories in a unique data set that represents multiple birth cohorts and has specific information on outcomes representing significant work disability. If similar trajectories emerge, this will speak to the robustness of how these patterns of productivity loss develop over time and will have implications for the use of the trajectories in research and practice. In addition, the inclusion of specific work disability outcomes will allow for a better understanding of differences across the trajectories in premature work withdrawal and the contribution of each trajectory toward the number of persons receiving permanent disability (PD) benefits from public programs.
METHODS Participants This study utilized data from the Panel Study of Income Dynamics (PSID).19 The PSID is a nationally representative longitudinal study of US households that gathers information on employment, income, health, and family demographics. A key informant, usually the head of the household, provides information about the entire family, including his or her spouse when present. The study started in 1968 with approximately 5000 households, representing more than 18,000 individuals. It has grown to about 9000 households and more than 24,000 individuals in the 2011 survey, which is the most recent survey year publically available. The sample of households in the PSID has continued to grow as children of the original households get married, have their own children, and form new, separate households that are added to the sample. Households have been surveyed annually until 1997 and then every other year after that point. In this study, we limit our sample to individuals who participated in at least six waves of the PSID from the ages of 25 to 44 years and who had valid responses on the questions used in the trajectory model, that are described in the next section. Because the PSID involves participants entering the study at various ages, the survey years representing ages 25 to 44 years were different across participants. The data were restructured so that each wave corresponds to an age instead of a survey year, similar to other previous research.17,20,21 We further restricted the sample to individuals who participated in the surveys at the ages of 25 or 26 years and again at the ages of 43 or 44 years, which roughly reflects the ages in the first and last waves used in the prior trajectory model, yielding a sample of 4960 unique cases. Included in our sample are heads of households and partners of the heads. These data restrictions roughly reflect those used in the previous study by Besen and Pransky, which identified productivity loss trajectories in the NLSY79.17
Measures Productivity Loss In each survey, the heads of households were asked whether they had a physical or nervous condition that limits the type of work or the amount of work they can do. This question was asked of all heads of households starting in 1968, and then of all spouses in 1978 and from 1981 onwards. Responses were coded 1 for yes and 0 for no. Productivity loss was asked as a single question in 1968 and from 1972 onwards; however, from 1969 to 1971, participants were asked, “Do you have any physical or nervous condition that limits the kind of work you can do?” and “Do you have any physical or nervous condition that limits the amount of work you can do?” We combined these items and coded individuals as yes if they responded “yes” to either question and no if they responded “no” to both questions. 830
Trajectory Baseline Covariates The trajectory model was adjusted for sex, race, and education. Sex was coded 1 for female and 0 for male. Race was coded 1 for white and 0 for nonwhite. Education was coded as a continuous variable, indicating the maximum number of years of education observed across waves that an individual participated in the PSID.
Work Disability Outcomes We assessed work disability, using three methods. First, starting in 1976, when heads of households were asked about their work status with the question “We would like to know about what you do-–are you working now, looking for work, retired, a student, a housewife, or what?”, one of the response options was “permanently disabled.” Prior to 1976, “permanently disabled” was not treated as an independent response option, and so for this study, we use only responses from 1976 onwards. In 1979, “permanently disabled” was included as a response option in reference to spouse’s work status as well. Responses were coded as 1 for permanently disabled or 0 for any other option. The other options included “working now,” “only temporarily laid off,” “looking for work, unemployed,” “retired,” “housewife,” “student,” and “other.” We refer to this measure as PD. The second method for evaluating work disability was based on receiving social security. Starting in 1986, a separate question was used for heads of households and spouses about receiving social security income. If individuals report receiving social security, they are asked a follow-up question about the type of social security, with a response option of “disability.” Responses were coded 1 for receiving SSDI and 0 for not receiving SSDI. We refer to this measure as SSDI. As a final method for assessing work disability, we combined the responses from the first two work disability items. Individuals’ responses were coded as 1 if an individual responded that he or she was permanently disabled and/or was receiving SSDI and 0 if an individual did not respond affirmatively to either question. Because the social security disability question was not assessed until 1986, from 1976 to 1985, the responses for this method of assessing work disability were identical to the responses to the work status question. We refer to this measure as any long-term disability (ALTD).
Analytic Strategy We conducted our analyses in two stages. In the first stage, we estimated the trajectory model, using the user-written program “traj” for STATA, which is used for latent class growth analysis.22 Latent class growth analysis is a type of growth mixture modeling where distinct subgroups of individuals after similar development trajectories are identified.23 In this type of analysis, the number of trajectories, as well as the shape of the trajectories, is prespecified. Because our trajectory analysis was aimed at replicating previous findings, we used the same specifications as in the study by Besen and Pransky.17 This involved estimating a five-group trajectory model using the logit option to evaluate the probability of productivity loss where all trajectories had a quadratic shape. The model was assessed over the age range 25 to 44 years, as this roughly corresponded to the age range in the prior trajectory analysis and represents the majority of prime working years. In the trajectory analysis, a new variable was generated that grouped individuals into the different trajectories based on the maximum likelihood probability rule.24,25 This grouping variable was then used in subsequent analyses. In the second stage of the analyses, we focused on differences in the work disability outcomes across the productivity loss trajectories. We examined the work disability outcomes for two separate age ranges, first within the trajectory age range of 25 to 44 years, and then after the trajectory period, by examining ages 45 to 64 years. Within each given age, there was a significant number of missing values as the survey switched from annual to biennial in 1997, the
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questions relating to work disability were not asked in every survey, and in many cases individuals did not participate in every survey, either because of study attrition or in the case of the analyses for the age range after the trajectory period, some individuals had not yet reached those ages. To include as many individuals as possible in the second stage of analyses, we created aggregate measures of work disability, which combined responses to the disability questions for the two age ranges (25 to 44 years and 45 to 64 years), respectively. For PD, if individuals ever reported being permanently disabled from the ages of 25 to 44 years, they were coded as a 1. If individuals never reported being permanently disabled during those ages, they were coded as 0. An aggregate work disability measure was also created for the trajectory follow-up age range of 45 to 64 years using the same coding strategy. An identical coding strategy was used for individuals receiving SSDI and for the ALTD measure. To evaluate the prevalence of work disability in the two age ranges, we also created variables for the three work disability outcomes (PD, SSDI, and ALTD) that represented the percentage of waves within the two age ranges where individuals responded to the work disability questions and had affirmative responses. A separate prevalence
variable was created for each of the work disability outcomes for the two age ranges. In cases where individuals did not respond to a work disability question within a given age range, those individuals were excluded from the second stage of analyses. Supplemental Digital Content Tables 1 (available at: http://links.lww.com/JOM/A206) and 2 (available at: http://links.lww.com/JOM/A207) provide information on the number of waves that individuals responded to the work disability questions for the two age ranges. Logistic regression models were used to examine the relationships between membership in the different trajectory groups and the odds of ever reporting being permanently disabled and/or receiving SSDI benefits. Separate models were estimated for ages 25 to 44 years and ages 45 to 64 years, as well as for the three work disability outcomes. These models were adjusted for sex, race, and education. To examine differences in the prevalence of work disability across the trajectory groups, analysis of covariance was used. We used separate models for each of the work disability outcomes and for each of the two age ranges. The covariates included were sex, race, and education. All analyses were conducted using STATA 13.1 (StataCorp LP, College Station, TX).
TABLE 1. Logistic Regression Model for Work Disability Outcomes From the Ages of 25 to 44 Yearsa Permanent Disability, (N = 4960) OR Low risk (LR) Late onset (LO) Early onset (EO) High risk (HR) Female White Education Intercept
Social Security Disability Income, (N = 4960) 95% CI
OR
Any Long-Term Disability, (N = 4960) 95% CI
OR
95% CI
12.79*** 8.40–19.47 3.94*** 2.07–7.50 9.20*** 6.38–13.26 28.31*** 19.36–41.40 10.81*** 6.64–17.59 18.40*** 13.25–25.56 95.33*** 62.77–144.78 45.70*** 28.68–72.82 62.26*** 42.86–90.44 89.22*** 55.12–144.42 42.49*** 24.74–72.99 57.99*** 37.14–90.55 1.42** 1.09–1.84 0.79 0.56–1.11 1.19 0.93–1.51 0.35*** 0.27–0.45 0.46*** 0.33–0.64 0.33*** 0.26–0.42 0.82*** 0.77–0.87 0.91* 0.84–0.99 0.83*** 0.78–0.88 0.02*** 0.01–0.02 0.01*** 0.01–0.02 0.03*** 0.02–0.04 Wald Test Comparisonsb Wald Test Comparisonsb Wald Test Comparisonsb EO, HR > LO, LR; LO > LR EO, HR > LO, LR; LO > LR EO, HR > LO, LR; LO > LR
*P < 0.05; ** P < 0.01; ***P < 0.001. a The no-risk trajectory is the reference group for the models. b All comparisons are based on Wald tests significant at P < .05. CI, confidence interval; OR, odds ratio.
TABLE 2. Prevalence of Experiencing Work Disability Outcomes From the Ages of 25 to 44 Years Prevalence
Disability Outcome
No Risk (NR) (n = 3763)
Low Risk (LR) (n = 412)
Late Onset (LO) (n = 432)
Early Onset (EO) (n = 225)
High Risk (HR) (n = 128)
F Test
Permanent Disability
0.4%
2.0%
3.3%
12.3%
18.2%
462.43***
Social Security Disability Income
0.3%
1.0%
1.9%
10.3%
12.4%
190.41***
Any Long-Term Disability
0.5%
2.5%
3.7%
14.3%
21.5%
498.67***
Pairwise Comparisona HR > EO, LO, LR, NR; EO > LO, LR, NR; LO > LR, NR; LR > NR HR > EO, LO, LR, NR; EO > LO, LR, NR; LO, LR > NR HR > EO, LO, LR, NR; EO > LO, LR, NR; LO > LR, NR; LR > NR
***P < 0.001. a All comparisons are based on significance at P < .05. EO, early onset; HR, high risk; LO, late onset; LR, low risk; NR, no risk.
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RESULTS
initially had a slight increase in the probability of productivity loss from ages 25 to 30 years and then remained relatively high thereafter.
Descriptives In the trajectory sample, 43% of the sample was female and 67% were white. The large majority of the sample (83%) had 12 or more years of education. Within the trajectory age range of 25 to 44 years, the number of waves individuals participated in ranged from 6 to 20, with less than 3% of the sample participating in fewer than 10 waves. The survey year in which participants first entered the trajectory age range went from 1968 until 1993. For the trajectory follow-up age range of 45 to 64 years, the number of waves individuals participated in ranged from 0 to 15 waves, with about half of the sample (51%) completing fewer than five waves.
Productivity Loss Trajectories A five-group trajectory model was found to fit the data. The trajectories were roughly the same as those identified by Besen and Pransky,17 using the NLSY79, and in the presentation of the current trajectory model, we have applied the same labels as previously used. The trajectories are plotted in Fig. 1. The trajectories from the previous study are presented in Supplemental Digital Content Figure 1 (available at: http://links.lww.com/JOM/A208). A posterior probability of 0.80 per a trajectory group for those assigned to that respective trajectory indicates a good model fit.26 The mean posterior probability per trajectory ranged from 0.84 to 0.97. In addition, the mean posterior probability for individuals not assigned to the given trajectory was less than 0.10, further showing a good model fit. The no-risk trajectory characterized three quarters of the sample (75.9%) and showed a stable zero probability of productivity loss over time. The low-risk trajectory accounted for 8.3% of the sample and had a relatively low probability of productivity loss over time, with a slight increase in the probability up to the age of 32 years and then a slight but steady decrease after that point. The late-onset increasing risk trajectory characterized 8.7% of the sample, showing an initially low probability of productivity loss, which began quickly increasing around the age of 35 years. We also identified an earlyonset increasing risk trajectory that had an initially low probability of productivity loss followed by a steadily increasing probability beginning around the age of 40 years and then leveling off after that point. This trajectory accounted for 4.5% of the sample. The final group was a high-risk trajectory representing 2.6% of the sample, which
Disability Outcomes for Ages 25 to 44 Years (Trajectory Age Range) Using the trajectory grouping variable identified in the trajectory model, we examined differences in the odds of experiencing different disability outcomes across the trajectory groups for the age range within the trajectory period of 25 to 44 years. The results of the logistic regression models for the 25- to 44-year age range are presented in Table 1. The no-risk group was used as the reference group for analyses. We also conducted Wald tests with one degree of freedom to compare the nonreference trajectory groups in the logistic regression models. Across the disability outcomes (PD, SSDI, and ALTD), a similar pattern was observed where the odds of ever experiencing the specific type of disability within the ages 25 to 44 years were highest for the high-risk and early-onset trajectories, followed by the late-onset trajectory and then the lowrisk trajectory. The odds of experiencing the different work disability outcomes were between 42 and 89 times higher for the highrisk trajectory, 46 to 95 times higher for the early-onset trajectory, 11 to 28 times higher for the late -onset trajectory, and 4 to 13 times higher for the low-risk trajectory relative to the no-risk trajectory. The confidence intervals for the odds ratios were somewhat large, suggesting that the precision of the odds ratios be interpreted cautiously. To further examine differences across the trajectory groups, we assessed differences in the prevalence of experiencing the work disability outcomes within the waves of the study in which individuals participated between the ages of 25 and 44 years. As shown in Table 2, across all three work disability measures, we found the high-risk trajectory to have a greater prevalence of waves experiencing work disability than all other trajectories, ranging from a high of 21.5% of the waves for having ALTD and a low of 12.4% for receiving SSDI. The early-onset risk trajectory was also found to have a greater prevalence for the three work disability outcomes relative to the late-onset, low-risk, and no-risk trajectories, ranging from 10% of the waves to 14% of the waves. Both the no-risk and low-risk trajectories had a relatively low prevalence of waves with work disability across the three types, with prevalence between 1% and 3% for the low-risk trajectory and less than 1% for the no-risk trajectory.
Disability Outcomes for Ages 45 to 64 Years (Trajectory Follow-Up Age Range)
FIGURE 1. Trajectories of the probability of productivity loss across the ages of 25 to 44 years in the Panel Study of Income Dynamics. 832
We replicated the analyses presented earlier for the age range after the trajectory period, specifically for the ages 45 to 64 years. The results of the logistic regression models are presented in Table 3. The odds of experiencing the different disability outcomes (PD, SSDI, and ALTD) in the follow-up age range were much smaller than those for the odds within the trajectory age range; however, several differences still emerged. Relative to the no-risk trajectory, the odds of experiencing the different disability outcomes were highest for the early-onset trajectory ranging from 11 to 14 times higher, followed by the high-risk trajectory ranging from 7 to 10 times higher, and the late-onset trajectory ranging from 6 to 7 times higher. The odds for the low-risk trajectory were around two times higher than those for the no-risk trajectory. The results for the analyses of the prevalence of waves experiencing work disability for the age range 45 to 64 years are presented in Table 4. We found that in roughly a third of the waves in which individuals participated, that individuals in the high-risk and early-onset trajectories experienced some type of work disability. For receiving SSDI specifically, the prevalence was a bit lower at about a fifth of the waves for the high-risk and early-onset trajectories. The prevalence of experiencing work disability for the late-onset trajectory C 2015 American College of Occupational and Environmental Medicine
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JOEM r Volume 57, Number 8, August 2015
Relationship Between Productivity Loss Trajectories and Work Disability Outcomes
TABLE 3. Logistic Regression Model for Work Disability Outcomes From the Ages of 45 to 64 Yearsa Social Security Disability Income, (n = 4293)
Permanent Disability, (n = 4293)
Low risk (LR) Late onset (LO) Early onset (EO) High risk (HR) Female White Education Intercept
Any Long-Term Disability, (n = 4293)
OR
95% CI
OR
95% CI
OR
95% CI
2.26*** 6.75*** 13.92*** 9.83*** 1.34** 0.40*** 0.79*** 0.08*** Wald Test Comparisonsb EO > LO, LR; HR, LO > LR
1.58–3.23 5.08–8.97 9.88–19.62 6.31–15.33 1.07–1.67 0.32–0.50 0.75–0.84 0.06–0.10
1.67* 6.14*** 10.82*** 6.98*** 1.31* 0.56*** 0.81*** 0.05*** Wald Test Comparisonsb EO > LO, LR; HR, LO > LR
1.09–2.56 4.55–8.30 7.61–15.41 4.36–11.19 1.03–1.67 0.44–0.71 0.77–0.86 0.04–0.07
1.94*** 7.29*** 13.28*** 10.25*** 1.38** 0.41*** 0.80*** 0.09*** Wald Test Comparisonsb EO > LO, LR; HR, LO > LR
1.37–2.74 5.58–9.53 9.50–18.56 6.66–15.76 1.12–1.70 0.33–0.51 0.76–0.84 0.08–0.11
*P < 0.05; ** P < 0.01; ***P < 0.001. a The no-risk trajectory is the reference group for the models. b All comparisons are based on Wald tests significant at P < .05. CI, confidence interval; OR, odds ratio.
TABLE 4. Prevalence of Experiencing Work Disability Outcomes From the Ages of 45 to 64 Years Prevalence No Risk (NR) (n = 3261)
Low Risk (LR) (n = 356)
Late Onset (LO) (n = 377)
Early Onset (EO) (n = 191)
High Risk (HR) (n = 108)
F Test
Pairwise Comparisona
Permanent Disability (PD)
2.9%
5.4%
16.8%
30.5%
24.1%
200.05***
Social Security Disability Income (SSDI) Any Long-Term Disability (ALTD)
2.0%
3.4%
12.3%
23.9%
20.8%
160.92***
3.7%
6.6%
21.7%
36.7%
32.6%
250.62***
EO > HR, LO, LR, NR; HR > LO, LR, NR; LO > LR, NR; LR > NR EO, HR > LO, LR, NR; LO > LR, NR EO, HR > LO, LR, NR; LO > LR, NR; LR > NR
Disability Outcome
*P < 0.05; ** P < 0.01; ***P < 0.001. a All comparisons are based on significance at P < .05.
ranged between 12% and 22% of the waves in which individuals participated across the different types of work disability. The prevalence was somewhat lower for the no-risk and low-risk trajectories, ranging from 3% to 7% for the low-risk trajectory and ranging from 2% to 4% for the no-risk trajectory.
DISCUSSION This study evaluated longitudinal trajectories of the probability of experiencing health-related productivity loss from the ages of 25 to 44 years using the PSID. Understanding the various pathways of changing productivity loss and disability status over time may help provide a longer-term perspective on disability issues and when to best target and provide disability prevention strategies. Using the trajectories identified with the PSID, we examined differences across the trajectories in work disability outcomes for the age range within the trajectory period of 25 to 44 years, as well as the age range after the trajectory period from the ages 45 to 64 years. Several interesting findings emerged. In line with a previous study that identified five trajectories of health-related productivity loss using the NLSY79,17 we also found a five-group trajectory model with remarkably similar patterns when
using the PSID. In this trajectory model, there was a no-risk trajectory that had a constant zero probability of productivity loss, a low-risk trajectory that also had a relatively low probability of productivity loss, although it was slightly higher than that in the no-risk trajectory, two increasing risk trajectories, and a high-risk trajectory that had a mostly stable high probability of productivity loss across the ages of 25 to 44 years. The first increasing risk trajectory was the earlyonset trajectory that started with a low probability of productivity loss but the probability began quickly increasing around the age of 30 years. The late-onset increasing risk trajectory also started with a relatively low probability of productivity loss, but in this trajectory, the probability did not begin to quickly increase until closer to the age of 35 years. These five trajectories very closely matched those previously identified with one exception from the ages 40 to 44 years. In this study, the early-onset trajectory starts to level out at a high probability of productivity loss, but it does not actually turn and start decreasing between the ages of 40 to 44 years. In contrast, in their previous study, the authors17 found a slight turning point during those years. This difference may be negligible though as the probability of productivity loss for the early-onset trajectory in both studies remains high.
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Besen and Pransky
Regarding the work disability outcomes, within the ages of 25 to 44 years, the productivity loss trajectories were found to be highly related to differences in work disability outcomes. In terms of receiving SSDI, the low-risk, late-onset, early-onset, and high-risk trajectories were all more likely to have received SSDI one or more times from the ages of 25 to 44 years. The early-onset and high-risk trajectories were also more likely to have received SSDI than either the low-risk or late-onset trajectories. Both the early-onset and highrisk trajectories received SSDI in more than 10% of the waves they participated in from the ages of 25 to 44 years, whereas the other three trajectories received SSDI in less than 2% of waves. In terms of reporting being permanently disabled, a similar pattern emerged, with the high-risk group reporting being permanently disabled in close to 20% of the waves from the ages of 25 to 44 years, and the early-onset group reporting PD in more than 10% of the waves. In contrast, the no-risk group reported PD in less than 1% of waves. Membership in the different trajectories was also found to be highly related to differences in the work disability outcomes from the ages of 45 to 64 years. Relative to the no-risk trajectory, the other four trajectories all had a greater likelihood of receiving SSDI or being permanently disabled in at least 1 year between the ages of 45 to 64 years. The early-onset trajectory also had a greater likelihood of receiving SSDI or being permanently disabled in at least 1 year than the late-onset and low-risk trajectories. In addition, both the high-risk and late-onset trajectories had a greater likelihood of receiving SSDI or being permanently disabled in at least 1 year than that low-risk trajectory. For both the early-onset and high-risk trajectories, individuals experienced some type of long-term disability in approximately a third of the waves they participated in from the ages of 45 to 64 years. In contrast, the late-onset trajectory experienced ALTD in only about a fifth of the waves they participated in and the low-risk and no-risk trajectories experienced ALTD in less than 10% of the waves. Research has not previously examined the relationship between health-related productivity loss trajectories and work disability outcomes; however, our findings regarding differences in the likelihood of experiencing ALTD across the trajectories are in line with previous studies indicating a relationship between aspects of productivity loss and work disability outcomes. For example, studies have shown that previous sick leave, which may be considered an aspect of productivity loss in regard to absenteeism, is a strong predictor of subsequently being granted a disability pension.27–30 One study found that a considerable number of individuals with sick leave related to arthritis ultimately become permanently disabled from work.31 Other research has illustrated a relationship between work ability, which is closely linked to work limitation, and later receipt of a disability pension.32,33 Much of this research is conducted outside of the United States in countries with well-established disability pension systems such as the Netherlands and Denmark; thus, this study helps illustrate consistent findings in the US context where the disability system is somewhat different.
Implications There are several important implications of the findings of this study. First, this study illustrates that there are multiple patterns for productivity loss developing across the lifespan. As can be seen in the high-risk trajectory, for some individuals there is a constant high probability of productivity loss, which suggests that there was not a single event in adulthood, after which an individual had permanent productivity loss, rather these individuals likely have lifelong conditions that impact work ability and eventually lead to permanent withdrawal from the labor force. In contrast, for other individuals such as those in the two delayed onset trajectories, the probability of productivity loss begins quickly increasing after a certain point, in this case either age 30 or 35 years. It is possible that in these trajectories, there was a single event such as a specific diagnosis after 834
which work ability was permanently impacted. Unfortunately, in this study we do not have information on the exact cause of individuals’ productivity loss and thus we are not able to confirm whether the reasons for productivity are specific to the different trajectories, but previous research has shown that the incidence of chronic illness differs across the trajectories.18 A second implication has to do with the robustness of our findings relating to the different temporal patterns. It is rare that extensive longitudinal data covering more than a 20-year span from the ages of 25 to 44 years would exist with multiple populations and with comparable measures on productivity loss. Nevertheless, in the United States there are two nationally representative ongoing longitudinal studies that make this possible: the NLSY79 and the PSID. The trajectories identified in this study using the PSID very closely replicate the findings of a previous longitudinal study that used the NLSY79.17 As such, we believe that this study helps support both the validity and reliability of these productivity loss trajectories. A final implication relates to our findings showing differences in key work disability outcomes, including receiving SSDI. In the United States, both the number of beneficiaries in the social security disability program and the cost of benefits for recipients have been increasing over time.34 In fact, over the past decade, the cost of SSDI has doubled reaching an all-time high of $144 billion in 2014 and this is a federal program paid for by taxpayers.35 The SSDI fund is expected to be exhausted by 2016 raising concerns for policymakers. The results of this study have implications for identifying individuals early on who may be at risk of ultimately receiving SSDI. Being in either the high-risk or early-onset trajectory was strongly related to receiving SSDI at some point from the ages of 25 to 64 years. As such, these workers may be a potential group for intervention to prevent becoming permanently disabled. Future research utilizing these trajectories is needed to further identify baseline factors that differ across the trajectories that may be used for finding individuals at risk for poor work disability outcomes.
Limitations Despite our use of a large, nationally representative longitudinal data set covering approximately 5000 individuals, there are a few important limitations to acknowledge. A major limitation with the PSID is that there is no information available about what specific health conditions are responsible for the health-related productivity loss. As such, we do not know if there are differences across trajectories in what causes the productivity loss and whether the same conditions cause the productivity loss at each given age. Another limitation has to do with the measures of work disability. These measures were not asked in every wave. This resulted in the incomplete capture of information on whether individuals reported being permanently disabled or receiving SSDI. Although we found large differences across the trajectories in the work disability outcomes, the magnitude of the differences may have been biased by the lack of information on work disability at certain ages for certain trajectories. Because the questions were asked or not asked at a given age in the same manner across the trajectories, the bias would have been evenly distributed across groups. This does seem to be the case as there were similar percentages of individuals in the different trajectories having answered the work disability questions in similar frequencies. For the work disability outcomes between the ages of 45 and 64 years, several individuals had not yet reached the ages in this range. As a result, it will be important to continue to update the analyses as more waves of data become available. As with any longitudinal study, there may have been historical changes relating to the variables in the study that make comparison of the variables at different time points difficult. For example, changes in legislation concerning work disability from 1968 to 2011 may have impacted our findings. Unfortunately, in the analyses there is no way to control for this. Nevertheless, the impact of historical effects may
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Relationship Between Productivity Loss Trajectories and Work Disability Outcomes
have been partially mitigated as multiple cohorts were included in our sample. For example, some individuals in the sample may have turned 25 years in 1968, whereas others turned 25 years in 1979, meaning that they would have been subject to different historical influences at any given age. Future research is needed to examine the influence of changes in legislation and other policies that may influence work disability over time.
CONCLUSIONS Health-related productivity loss costs employers billions of dollars each year. As such gaining a greater understanding of how productivity loss develops over one’s working years is of significance. This study identified five unique trajectories of productivity loss using the PSID which were found to closely mirror trajectories that were previously identified using a different data source. The likelihood of receiving SSDI or being permanently disabled at some point from the ages of 25 to 64 years was found to vary greatly across the different trajectories. The trajectories from this study may be useful to future research in identifying individuals at risk of becoming permanently disabled.
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