the administrative records from a large , private workers compensation insurance company in the united states were used in this study . these claims come from various different organizations , industries , company sizes , and geographic locations . all claims with complete data from january 1 , 2002 until december 31 , 2008 were assessed for inclusion . only claims with at least 1 day of compensated lost work time were included . lost work time included both days of temporary partial disability ( tpd ) and days of temporary total disability ( ttd ) . claims were followed for 1 year from the date at which lost work time began or until indemnity payments finished if that occurred within a year . several restrictions were applied to the claims ( initial pool  =  427,571 ) . for claimants who had multiple claims within a single calendar year from 2002 to 2008 , only the first claim within the calendar year was included in analyses ( 13,222 excluded ) . this was done to ensure that we only followed a single claim from a claimant within 1 calendar year . claimants who received a lump sum payment within 1 year of claim initiation were also excluded ( 5701 excluded ) . in several instances , claimants first received compensation for lost work time more than 1 year after claim initiation . the sample was restricted to only include claims wherein lost work time first occurred within 1 year of claim initiation ( 6038 excluded ) . finally , some claimants experienced multiple episodes of lost work for a single claim resulting from the same condition . this occurred in cases wherein an individual went back to work after an injury / illness for some time but then had to go back out of work again as a result of the same condition . for the current study , claimants were considered to have multiple episodes of lost work time when they returned to work for at least 14 days before having to go back off again . cases wherein the individual returned to work for less than 14 days before going back out were considered a single episode . age and tenure at the time of claim initiation were the main predictor variables for the analyses . the outcome variable was the length of disability , calculated based on the date that a claimant first received tpd or ttd until the date at which tpd or ttd ended . tpd or ttd were considered to have ended when no paid disability days were taken for at least 14 calendar days consecutively . when the length of disability exceeded 1 year , which occurred in 28,733 claims , the value for the length of disability was censored at 365 days . to address issues with normality , several variables that might confound the relationship between age , tenure , and length of disability were included in the analyses . these variables included gender , annual income , litigation status , and year of injury / illness . the first 15 were in increments of $ 10,000 ( eg , $ 0 to $ 9999 ) . litigation status was coded 1 if the insurer assigned an attorney to the claim and 0 if not . a series of dichotomous variables was used to represent the year of injury / illness with 2002 as the reference year . the crossed effect between industry and the diagnosis chapter industry was categorized into 10 groups including the following : ( 1 ) agriculture , forestry & fishing , ( 2 ) mining , ( 3 ) construction , ( 4 ) manufacturing , ( 5 ) transportation , communications , electric , gas , & sanitary services , ( 6 ) wholesale trade , ( 7 ) retail trade , ( 8) finance , insurance , & real estate , ( 9 ) services , and ( 10 ) public administration . the most commonly used international classification of diseases , ninth revised edition ( icd-9 ) diagnosis appearing in the claimant 's medical file for the first 15 days of medical bills was used as the primary diagnosis for the claim . the crossed - effect approach was selected instead of treating diagnosis chapter and industry separately because it is likely that certain diagnoses are more prevalent in some industries than others . in addition , the impact of specific diagnoses on the length of disability is likely to be dependent on the industry in which an individual works . for example , the length of disability might be shorter following a leg fracture in the finance , insurance , & real estate industry than in the construction industry . by using a crossed - effect approach we are better able to take this into account . age and tenure at the time of claim initiation were the main predictor variables for the analyses . the outcome variable was the length of disability , calculated based on the date that a claimant first received tpd or ttd until the date at which tpd or ttd ended . tpd or ttd were considered to have ended when no paid disability days were taken for at least 14 calendar days consecutively . when the length of disability exceeded 1 year , which occurred in 28,733 claims , the value for the length of disability was censored at 365 days . to address issues with normality several variables that might confound the relationship between age , tenure , and length of disability were included in the analyses . these variables included gender , annual income , litigation status , and year of injury / illness . the first 15 were in increments of $ 10,000 ( eg , $ 0 to $ 9999 ) . litigation status was coded 1 if the insurer assigned an attorney to the claim and 0 if not . a series of dichotomous variables was used to represent the year of injury / illness with 2002 as the reference year . the crossed effect between industry and the diagnosis chapter was estimated using random effects in the analyses . industry was categorized into 10 groups including the following : ( 1 ) agriculture , forestry & fishing , ( 2 ) mining , ( 3 ) construction , ( 4 ) manufacturing , ( 5 ) transportation , communications , electric , gas , & sanitary services , ( 6 ) wholesale trade , ( 7 ) retail trade , ( 8) finance , insurance , & real estate , ( 9 ) services , and ( 10 ) public administration . the most commonly used international classification of diseases , ninth revised edition ( icd-9 ) diagnosis appearing in the claimant 's medical file for the first 15 days of medical bills was used as the primary diagnosis for the claim . the crossed - effect approach was selected instead of treating diagnosis chapter and industry separately because it is likely that certain diagnoses are more prevalent in some industries than others . in addition , the impact of specific diagnoses on the length of disability is likely to be dependent on the industry in which an individual works . for example , the length of disability might be shorter following a leg fracture in the finance , insurance , & real estate industry than in the construction industry . by using a crossed - effect approach we are better able to take this into account . to analyze the relationship between age , tenure , and the length of disability , random - effects models were utilized instead of ordinary least squared regression models , due to the non - independence of observations across the major diagnosis chapters and industry groupings . using a crossed - effect approach , random effects for each diagnosis chapter by industry grouping only pairings with at least 20 claims per pairing were included in the analyses . in the first stage of the analyses , possible nonlinearity in the relationship between age and the length of disability was examined . the linear term for age was added to the first model . in the second model , the squared term for age was added . in the second stage of the analyses , the linear and nonlinear age and tenure terms reaching statistical significance were then included in a combined model with both age and tenure . in the final stage of the analyses , analyses were estimated using stata 13 ( stata corporation , college station , tx ) . the analyses presented have a large sample size and thus a p value of less than 0.001 was considered statistically significant . in addition , we present the predicted lengths of disability for the different statistically significant relationships addressed . we did not use a specific cutoff for determining the meaningfulness ( clinical significance ) of a difference in the predicted lengths of disability , as this number likely varies dependent on the stakeholder group ( ie , employers , policy makers , or clinicians ) . of all claims ( 361,754 ) , 31% were for women , half ( 50% ) had an annual income greater than $ 30,000 , and approximately a quarter ( 27% ) were involved in litigation . the number of claims by year declined from 58,793 claims in 2002 to 47,097 claims in 2008 . the largest industries represented in the claims were manufacturing ( 23% ) , transportation , communications , electric , gas , & sanitary services ( 23% ) , and services ( 22% ) . the most common diagnosis chapters were injury and poisoning ( 53% ) and diseases of the musculoskeletal system ( 29% ) . length of disability ranged from 3 days to 365 days , with an average of 88 days . the age of claimants in the sample ranged from 18 to 80 years , with an average of 41 years , and the length of tenure ranged from 0 to 30 years , with an average of 6 years . in our sample , the correlation between age and tenure was 0.38 ( p  <  0.001 ) . for the first stage of the analyses , the relationship between age and the length of disability was estimated . , we found that the relationship was slightly nonlinear ( figure 1 ) , with both the age and age - squared terms reaching statistical significance . the relationship changes very little when adjusted for tenure ( model 5 ) than when not adjusted for tenure ( model 2 ) . when adjusted for tenure , the predicted length of disability varies by approximately 18 days across ages 18 to 80 , ranging from 32.3 days at age 18 to 50.9 days at age 80 . regarding the adjustment of the model for tenure , we compared the age coefficients from model 2 , with the age coefficients from model 5 using a wald test . we found that the age coefficients were statistically similar across the models (   =  3.71 , p  >  0.05 ) . plot of the relationship between age and the length of disability when adjusted and unadjusted for tenure . this figure is based on predicted values for the length of disability at different ages . in the second stage of the analyses , , we found a linear relationship with the length of disability , with the tenure - squared term ( model 4 ) not reaching statistical significance . the tenure relationship was estimated unadjusted for age ( model 3 ) and adjusted for age ( model 5 ) . we found the relationship to be quite different when the model was adjusted for age . a wald test comparing the tenure coefficients for the adjusted and unadjusted models revealed a significant difference (   =  49.82 , p  <  0.001 ) . the adjusted and unadjusted relationships are plotted in figure 2 . when the tenure - length of disability relationship was not adjusted for age , there was a positive relationship with the predicted length of disability increasing as tenure increased . the predicted length of disability ranged from a low of 42.1 days at 1 year of tenure to a high of 43.7 days at 20 years of tenure . in contrast , when the relationship was adjusted for age , the relationship became negative with the predicted length of disability decreasing as tenure increased . in this model , the predicted length of disability ranged from a high of 43.8 days at 1 year of tenure to a low of 40.3 days at 20 years of tenure . plot of the relationship between tenure and the length of disability when adjusted and unadjusted for age . this figure is based on predicted values for the length of disability at different lengths of tenure . in addition to examining the main effect relationships of age and tenure with the length of disability separately , we also investigated differences between the relationships in their relative strength . using a wald test , we compared the absolute values of the coefficients for age and tenure in the combined model ( model 5 ) . the results revealed that the age - length of disability relationship was considerably stronger than the tenure - length of disability relationship (   =  526.82 , p  <  0.001 ) . in the final stage of analyses , the interaction between age and tenure with the length of disability was estimated . a significant interaction was found between age and tenure , which is plotted in figure 3 following the procedure of aiken and west . the age - length of disability relationship was plotted for various different lengths of tenure so that variation in the relationship across tenure levels might be observed . this figure is based on predicted values for the length of disability at different ages and lengths of tenure . as seen in figure 3 , at low levels of tenure ( less than 5 years ) , the relationship between age and the length of disability is a slightly inverted u - shaped relationship wherein the length of disability increases with age until around age 70 at which point the length of disability then begins decreasing slightly up to age 80 . in contrast , at higher levels of tenure ( more than 10 years ) , the length of disability continuously increases with age . the positive relationship between age and the length of disability is greater as tenure increases . prior to age 70 , as tenure increased , the predicted length of disability decreased ; however , after age 70 , as tenure increased , the predicted length of disability began to increase . in general , the highest predicted length of disability was for the oldest workers with high tenure , whereas the shortest predicted length of disability was for younger workers with the lowest tenure . the values of tenure might be thought to be conditional on age as certain values of tenure are not possible at younger ages ( eg , 20 years of tenure at 30 years of age ) . a series of analyses were therefore conducted with this conditional relationship in mind by attempting to estimate models wherein the full sample of claimants has the potential to have any of the lengths of tenure regardless of their age . in the first model , we examined the interaction between age and tenure with tenure dichotomized into less than 2 years of tenure compared with 2 or more years of tenure . the results of this model were largely similar to the model with tenure measured continuously ( supplemental figure 1 ) . in the second model , we restricted the sample to claimants age 30 or older and we also restricted the sample to claimants with less than 10 years of tenure . as seen in supplemental figure 2 , a similar finding emerged as in the full model . due to the large number of claims ( n  =  28,733 ) with a length of disability greater than 365 days , sensitivity analyses assessed whether the study findings varied when those claims were not included in the model . all analyses were replicated on the 333,021 claims with a length of disability of less than a year . the results were found to be consistent within this subsample . as with the full sample , the age - length of disability relationship was found to be nonlinear , whereas the tenure - length of disability relationship was found to be linear . the findings for age did not change when the model was adjusted for tenure . for tenure , the relationship with the length of disability did reverse when adjusted for age . also , the age - length of disability relationship was found to be stronger than the tenure - length of disability relationship . finally , the interaction pattern between age and tenure was similar in the subsample model . this study examined a model of age , tenure , and the length of disability in a large sample of workers compensation claims from the united states with the goal of better understanding the complexity among these factors . for age and the length of disability , in general there was a positive relationship with the length of disability increasing as age increased and this relationship varied very little based on whether or not it was adjusted for tenure . over a 2.5 week difference in the predicted length of disability specifically , the relationship began to flatten around age 70 and the length of disability increased very little with age from 70 to 80 years . whereas few studies have explored possible nonlinearity in the age - length of disability relationship , most studies have found a generally positive relationship between the two . in the one study that did assess potential nonlinearity , the relationship was still linear , but in this previous study , the age range only extended to 65 . in the present study , the observed nonlinearity was primarily for workers over age 65 , which might explain the divergence in our results . it is possible that the plateauing of the age - length of disability relationship after age 65 reflects the healthy worker effect , in which as age increases , only . the lack of variability in the length of disability at older ages could be the result of only healthier workers still being in paid employment and therefore eligible for workers compensation or it could result from the oldest workers feeling the need to go back to work sooner to keep their jobs secure . although the positive relationship between age and the length of disability has been shown in previous studies , there has been little empirical work testing the reasons for this relationship . there are , however , several possible explanations , such as the increasing likelihood of having comorbidities with age that might complicate the recovery process and physical changes that occur with age that might increase recovery time . there might also be aspects of individuals working conditions that might influence the length of disability . employers might be more likely to offer accommodations to younger workers or to give more encouragement to younger workers to rtw quickly after injury . interestingly , the relationship differed greatly when it was adjusted for age compared with unadjusted for age . when unadjusted for age , there was a positive relationship such that as tenure increased , the length of disability also increased . although the reverse was true when adjusted for age  with the length of disability decreasing as tenure increased . this finding suggests that when the model did not include age , tenure was partially acting as a proxy for age . our finding of a negative relationship when adjusted for age is in line with previous research . we found approximately a 3-day decrease in the predicted length of disability going from 1 year to 20 years of tenure . it is important to note that although the relationship was statistically significant , even after the adjustment for age , the predicted length of disability only varied by a relatively small number of days over the range of tenure . from a clinical standpoint , a 3-day difference might not be very meaningful , in which case tenure would not be considered a primary factor in predicting the length of disability ; however , for employers and insurers who might be considering the length of disability for thousands of workers , even a 1 day difference in the length of disability can be important . in terms of the relative strength of the relationship with the length of disability for age and tenure , although both age and tenure remained statistically significant , age was found to be a stronger predictor of the length of disability than tenure . one possible explanation for this finding is that the mechanism behind the relationship between age and the length of disability , which might primarily reflect delayed recovery as a result of physiological changes associated with aging , has a greater impact on duration of disability than the mechanism behind the relationship between tenure and the length of disability . although open to conjecture , the tenure - length of disability relationship likely involves a desire to rtw quickly because of a stronger organizational attachment ; however , despite wanting to rtw quickly , older workers might need to remain out of work longer due to the additional time required for them to recover . this would result in the worker 's age having a greater impact on the length of disability than the worker 's length of tenure . we also found an interaction between age and tenure with the length of disability . at the youngest ages , we found very little variability in the length of disability across the tenure groups . this is logical as there is a far smaller range for the lengths of tenure for individuals who recently entered the workforce . in contrast , for midlife workers aged 45 to 50 , there was approximately a 4-day difference in the predicted length of disability across the tenure groups . the predicted length of disability was the shortest for midlife workers with high tenure compared with low tenure . this finding might reflect that in comparison to lower tenure midlife workers , workers in midlife that have been with their employers longer are more motivated to rtw quickly and know about the availability of resources at their organization , such as workplace accommodations , which facilitate a faster rtw . for workers in the typical retirement ages of 65 to 70 , the predicted length of disability was found to vary very little across the tenure groups , but by age 80 , the predicted length of disability varied by approximately a week , with lower tenure workers having a shorter predicted length of disability than high - tenure workers . it is possible that older workers with high tenure feel secure in their positions , and thus might not feel the need to rush back to work after a work - related injury / illness . in contrast , older workers with low tenure might hurry to rtw for fear of losing their jobs and being unable to find other employment due to their age . this might have contributed to differences in the length of disability across lengths of tenure in the oldest workers . the interaction between age and tenure found in our study is somewhat different from previous studies . in one study , for workers over the age of 53 , the number of days off of work following a work - related accident was higher for low - tenure workers than high - tenure workers . in this previous study , it is possible that this might contribute to the divergence of the findings as in our study , there was a turning point in the interaction between ages 50 and 80 . at age 50 , our findings were consistent with this previous study with the predicted length of disability being highest for low - tenure workers , but by age 80 the reverse was true . in another study , for homecare workers where the maximum age of participants was 64 years , the length of disability was found to be greater for the oldest workers with high tenure than those with low tenure , whereas in residential care workers , the oldest workers with medium tenure had the longest length of disability , followed by the high - tenure and then the low - tenure workers . this previous study focused on certified sickness absence as opposed to work - related injury / illness specifically that could account for the differences as certified sickness absence involves a large number of chronic medical conditions . first , the stronger relationship between age and the length of disability than between tenure and the length of disability has implications for research focused on the prognostic factors for rtw . by quantifying the magnitude of the relationships in a single model , we were able to show that age might be a more important factor to focus on than tenure . if tenure were to be included in models , the models should also include age , as the relationship between tenure and the length of disability actually reversed when adjusted for age . further , the age by length of disability relationship varied across tenure levels . from a clinical perspective , our results point to the need to gain a better understanding of the factors leading to the relationship between age and the length of disability . age - related changes in recovery time after any type of condition are likely to play a major role in this relationship , but to the extent that other factors might also influence this relationship might have the potential to inform interventions and treatment plans . for example , older workers might have a greater length of disability because suitable accommodations in the workplace are not made to facilitate returning to work . regarding the interaction between age and tenure , as the workforce continues to age and the nature of careers also evolves , it is important to consider the interplay between these two factors on the length of disability . up until the typical retirement age , for workers over the age of 50 , the length of disability was higher for workers with lower tenure . workers in midlife and those approaching retirement age who are new to their organizations might need additional support in the rtw process . these workers might be less familiar with the resources available to them and might not have strong organizational and supervisor relationships to rely on . from an intervention perspective , it might be important to identify what types of programs and policies would be most helpful in these workers rtw process . although our study had strengths including the use of a large number of workers compensation claims covering a wide range of employees of various ages and lengths of tenure in many different states and industries , there were important limitations to note . the large sample size afforded us the ability to examine the age and tenure interaction , but it also resulted in relationships being statistically significant despite there being relatively small differences in the predicted lengths of disability . when interpreting the results , it is important to consider what differences in the length of the disability are most meaningful to a given stakeholder group . due to our reliance on already existing administrative data , we were unable to include in our analyses variables such as comorbidities , relationships with coworkers , and availability of job accommodations . being able to have done so would likely have helped us to better understand the complexity of the age , tenure , and length of disability relationships . although it is a study strength that the age ranged from 18 to 80 years , individuals working after the traditional retirement years likely represent select groups of workers who delayed retirement , either due to financial necessity or personal preference . as such , the length of disability for the oldest workers might be influenced by factors beyond those at younger ages . in addition , in comparison with workers of other ages , there were relatively few workers over the age of 70 ( n  =  2492 ) , with workers aged 70 to 80 representing less than 1% of the total sample . with this in mind the length of disability was calculated based on the beginning and end of indemnity payments . in doing so , we assume that the end of indemnity payments coincides with rtw ; however , in the administrative data used in this study , there is no way to verify if this was indeed the case . it is possible that in certain cases , the end of indemnity payments actually signified an individual taking permanent disability or retirement . a final limitation was that the primary methodology used in this study did not fully account for the conditional relationship between age and tenure . at the youngest ages , we did supplemental analyses including only distributions of age and tenure that would be possible showing that our findings held under these conditions ; however , the results from the main analyses should be interpreted with this limitation in mind . the results of the current study pointed to a stronger relationship between age and the length of disability than for tenure and the length of disability . in terms of risk factors for longer work - disability durations , age seems like a more important factor than tenure ; however , there was variability in the age - length of disability relationship based on the length of tenure suggesting that tenure might still be an important aspect of the work - disability process . from a case management perspective , older workers might be a group in need of extra support as their rtw process seems to be delayed relative to younger workers . for some older workers , retirement is not an option due to financial necessity or needing to continue to have access to health insurance benefits beyond those provided by the government . such workers might feel unable to leave their jobs after a workplace injury / illness , and experience extra difficulty getting back to work . with the continued aging of the workforce and the changing nature of career paths , furthering our understanding of how and why age and tenure influence the current study was a first step in examining the interplay between age and tenure with the length of disability , but future research is necessary to uncover the mechanisms behind these relationships .