Work loss and work entry among persons with systemic lupus erythematosus: Comparisons with a national matched sample

Authors


  • Because Drs. Katz and Yelin are Editors of Arthritis Care & Research, review of this article was handled by the Editor of Arthritis & Rheumatism.

Abstract

Objective

To prospectively track work loss among those employed and work entry among those not employed in a cohort of persons with systemic lupus erythematosus (SLE), assess risk factors for these outcomes, and compare rates of the outcomes with a matched national sample.

Methods

The present study analyzed 4 years of data from the Lupus Outcomes Study (LOS), augmented by information on the local labor market from the Census Bureau and the Bureau of Labor Statistics. We used the Kaplan-Meier method to assess time from study initiation until work loss or work entry, and Cox proportional hazards regression to estimate factors affecting these outcomes. Finally, we compared rates of work loss and work entry in the LOS with rates in the Survey of Income and Program Participation (SIPP).

Results

At study initiation, 394 LOS participants (51%) were employed, of whom 92 (23.4%) experienced work loss. In multivariate analysis, older age, lower cognitive and physical functioning, and higher reports of depressive symptoms predicted work loss. In comparison with the SIPP sample, rates of work loss did not differ. Of the 376 LOS participants not employed, 76 (20.2%) experienced work entry. In multivariate analysis, less disease activity, fewer lung manifestations, better physical functioning, and shorter time since last employment predicted work entry. In comparison with the SIPP, rates of work entry were only lower between ages 35 and 55 years.

Conclusion

Until age 55 years, low rates of employment among persons with SLE may be due to lower rates of work entry rather than higher rates of work loss. Beyond age 55 years, both high rates of work loss and low rates of work entry contribute to low rates of employment.

INTRODUCTION

A series of studies using retrospective recall have established that persons with systemic lupus erythematosus (SLE) have low employment rates (1–4). For example, Partridge et al noted that almost half of persons with SLE stopped working within the first few years of disease (1). Mau et al (2) reported that, compared with an age- and sex-matched sample, persons with SLE with disease duration of a decade or longer were approximately one-third less likely to remain employed. Using the same data source as the current study, we noted that overall productivity among persons with SLE with an employment history declined by one-third between the year of diagnosis and the most recent year, an average of approximately 13 years later, with most of the loss occurring among those who stopped working completely rather than among those who reduced their hours of work (3). Panopalis et al also used the same data source to describe the impact that memory impairment has on employment (4).

The foregoing studies established the basic parameters of the impact of SLE on employment. However, due to their retrospective nature, they could not fully explore the role of SLE-related factors on employment dynamics. The present study advances the research of employment dynamics among persons with SLE because of the prospective nature of the data.

PARTICIPANTS AND METHODS

This analysis used data from the University of California, San Francisco Lupus Outcomes Study (LOS), augmented with contextual data from the US Bureau of the Census and the US Bureau of Labor Statistics, to assess the impact of sociodemographics, health status, and work characteristics on work loss and work entry among persons with SLE. We also compared their rates of work loss and work entry with those of a matched national sample from the Survey of Income and Program Participation (SIPP).

Data sources

The LOS is an ongoing, longitudinal study of 957 individuals with a confirmed SLE diagnosis based on American College of Rheumatology criteria (5, 6). Details about enrollment and data collection have been previously reported (3). Briefly, participants were recruited through health care settings (34%) and nonclinical sources, including patient support groups and conferences, newsletters, and Web sites; 73% are from California and the remainder are from 38 other states. LOS interviews have been conducted annually by telephone since September 2002. They include validated batteries capturing demographics and socioeconomic status, status of SLE, general health and functional status, mental and cognitive status, health care utilization, and employment. An average of 94% of eligible participants from each wave has been re-interviewed in the subsequent wave. Fourteen participants have withdrawn for health reasons, 38 have died, 75 have declined further participation, and 34 were lost to followup.

Secondary data sources

Employment rates were obtained from the 2000 US Census at the block group level (areas covering 600–3,000 persons) and matched to the LOS participants' home addresses through geocoding; details on this process have been previously published (7). County unemployment rates from 2003 were obtained from the Bureau of Labor Statistics' Local Area Unemployment Statistics file and matched to the LOS participants' counties of residence. National longitudinal data on employment status were accessed from the US Census Bureau SIPP 2001 panel, the most recent available (8). The SIPP panel includes 36,700 households interviewed every 4 months from February 2001 through January 2004. Employment status is available for every week during that period.

Study population

The present analysis incorporated the first 4 interviews of the LOS, collected between September 2002 and February 2007. Of the 957 participants, 770 (80%) were included in the analyses after excluding 70 (7%) participants without followup interviews, 77 (8%) who were age ≥65 years at baseline, 1 (0.1%) participant living outside the US, and 39 (4%) observations with missing data. The final sample was subset into those employed (n = 394) and not employed (n = 376) at baseline. All analyses were performed separately by employment status group.

Work loss and work entry

We calculated the duration of time until first reported work loss among those employed at baseline. Employment was defined as either working, with a job but not working, or doing any work for pay or profit in the last week. Anyone who neither had a job in the last week nor did any work for pay or profit was defined as not employed. Only the first incident of work loss was considered in this analysis, whether it was temporary or permanent. We estimated the month and year of work loss, using the exact date when available (in approximately half of the observations). For the remaining observations that provided an interval during which participants last worked rather than an exact date, we estimated time until work loss using the method outlined by Lindsey and Ryan for interval-censored data (9). We calculated the range of dates during which the work stoppage would have occurred, created variables to capture the beginning, midpoint, and end point of that interval, and ran all statistical analyses on each of the 3 variables. Because the results did not differ appreciably, we reported the results from the analysis using the midpoint of the interval.

Among those not working at baseline, we calculated duration of time until first work entry (i.e., first report of employment after baseline interview). We were able to calculate the exact time until work entry for approximately three-quarters of the participants. For the remainder, we estimated the interval until work entry using the method described above.

Predictors of work loss/entry

The framework for our analysis is based on a model of disability developed by Nagi (10) and extended by Verbrugge and Jette (11), which proposes a progression in the disablement process from underlying pathology (disease severity) to impairment (functional status), and finally, to disability in major life activities (work loss). Yelin et al (12) further extended the model of work disability to include societal and work-related factors. Following these models, potential predictors of work loss/entry were organized into 5 major sets: sociodemographic characteristics, neighborhood employment rate, disease severity, functional status, and characteristics of the job held at baseline (among those employed) or years since last employed (among those not employed). The specific variables within each set are listed in Tables 1 and 2. The models include numerous validated self-report health status measures: the Medical Outcomes Study (MOS) cognitive functioning scale (13), the Short Form 36 (SF-36) physical functioning scale (14), and the Center for Epidemiologic Studies Depression Scale (CES-D) (15). Self-report of specific disease manifestations in the LOS were validated using medical chart data, as outlined by Hersh et al (16). The measures of physical and cognitive demands at work were derived from the Health and Retirement Survey (17). The measure of high demands and low control is from the Job Content Questionnaire (18). Traditional employment refers to full-time regular employment on the day shift for a single employer; this definition has been used in previous analyses (19). Table 1.;

Table 1. Baseline characteristics and work loss among participants at baseline*
 Employed (n = 394)Work loss (n = 92)Did not leave work (n = 302)
  • *

    Categorical measures are the number (percentage); continuous measures are the mean ± SD (range). SLE = systemic lupus erythematosus.

  • P < 0.05.

  • Patient global rating of disease activity, range 0 (best) to 10 (worst).

  • §

    Center for Epidemiologic Studies Depression Scale (CES-D) (19), range 0 (best) to 60 (worst) (15).

  • Includes heart disease, diabetes, cancer, or lung problems (e.g., asthma, emphysema, and chronic bronchitis).

  • #

    Includes stroke, myocardial infarction, or other thromboses.

  • **

    Includes bronchoscopy, biopsy, or hemoptysis.

  • ††

    Includes biopsy, dialysis, or transplant.

  • ‡‡

    Medical Outcomes Study (MOS) cognitive functioning scale (20), range 0 (worst) to 100 (best) (13).

  • §§

    Physical functioning subscale of the Short Form 36 (SF-36) (21), range 0 (worst) to 100 (best) (14).

  • ¶¶

    Proportion of the adult population in census block group that is employed.

  • ##

    Full-time, full-year employment in a permanent position on a day shift for a single employer, not as a consultant (19).

  • ***

    From the Job Content Questionnaire, the conjoint presence of high levels of psychosocial job demands and low levels of control (17).

  • †††

    Includes walking; using stairs/inclines; sitting for long periods; stooping, crouching, or kneeling; lifting/carrying weights of 10 and/or 50 pounds; repeating the same hand motion ≥30 times/hour; bending over, twisting around; and using hand tools (17).

  • ‡‡‡

    Includes concentrating for long periods, interacting with other people, and using computers (18).

Demographic characteristics
 Age, years
  18–3489 (23)17 (18)72 (24)
  35–54247 (63)52 (57)195 (65)
  55–6458 (15)23 (25)35 (12)
 Female356 (90)84 (91)272 (90)
 Ethnicity
  White268 (68)59 (64)209 (69)
  Hispanic41 (10)11 (12)30 (10)
  African American22 (6)7 (8)15 (5)
  Asian/Pacific Islander43 (11)9 (10)34 (11)
  Other20 (5)6 (7)14 (5)
 Marital status
  Never married94 (24)25 (27)69 (23)
  Married/partner244 (62)55 (60)189 (63)
  Widowed, separated, divorced56 (14)12 (13)44 (15)
 Education
  High school graduate or less48 (12)17 (18)31 (10)
  Some college145 (37)35 (38)110 (36)
  College graduate201 (51)40 (43)161 (53)
Health characteristics
 Disease severity
  Duration of SLE, years11.3 ± 7.9 (0–46)10.4 ± 8.2 (1–37)11.6 ± 7.8 (0–46)
  SLE activity (patient global assessment)3.6 ± 2.9 (0–10)4.5 ± 3.1 (0–10)3.4 ± 2.8 (0–10)
  CES-D§13.4 ± 11.2 (0–52)18.1 ± 12.9 (0–52)12.0 ± 10.2 (0–48)
  ≥1 comorbid condition157 (40)46 (50)111 (37)
  Vascular events in past 5 years#45 (11)11 (12)34 (11)
  Lung manifestations in past 5 years**31 (8)11 (12)20 (7)
  Kidney manifestations in past 5 years††51 (13)11 (12)40 (13)
 Functional status
  MOS cognitive functioning scale‡‡62.8 ± 16.9 (17–83)55.9 ± 18.5 (17–83)64.9 ± 15.8 (17–83)
  SF-36 physical functioning scale§§72.1 ± 26.0 (0–10)62.4 ± 27.7 (0–100)75.1 ± 24.7 (5–100)
 Area-level measures, %
  County employment rate7 ± 2 (3–12)7 ± 2 (3–12)7 ± 2 (3–12)
  Neighborhood employment rate¶¶64 ± 10 (17–87)64 ± 9 (36–82)64 ± 10 (17–87)
Work characteristics
 Annual hours of work1,651.1 ± 803.4 (1–4,680)1,456 ± 908.5 (6–4,680)1,706.9 ± 763.2 (1–3,900)
 Job tenure, years6.8 ± 7.5 (0–43)6.8 ± 8.7 (0–43)6.9 ± 7.1 (0–35)
 Traditional employment##152 (39)31 (34)121 (40)
 High demands/low control***67 (17)17 (18)50 (17)
 Number of physical demands†††6.7 ± 2.7 (0–14)6.8 ± 3.0 (0–14)6.7 ± 2.7 (0–13)
 Number of cognitive demands‡‡‡4.9 ± 1.2 (0–6)4.7 ± 1.3 (0–6)5.0 ± 1.2 (0–6)
 Occupation categories
  Professional/managerial205 (52)47 (51)56 (19)
  Sales/technical/services74 (19)18 (20)14 (5)
  Crafts/operatives18 (5)4 (4)74 (25)
  Administrative support97 (25)23 (25)158 (52)
 Industry categories
  Professional services204 (52)45 (49)159 (53)
  Manufacturing/construction/extractive30 (8)10 (11)20 (7)
  Personal/business services41 (10)13 (14)28 (9)
  Miscellaneous119 (30)24 (26)95 (31)
Table 2. Baseline characteristics and work entry among participants not employed at baseline*
 Not employed (n = 376)Work gain (n = 76)Did not enter work (n = 300)
  • *

    Categorical measures are the number (percentage); continuous measures are the mean ± SD (range). SLE = systemic lupus erythematosus.

  • P < 0.05.

  • Patient global rating of disease activity, range 0 (best) to 10 (worst).

  • §

    Center for Epidemiologic Studies Depression Scale (CES-D) (19), range 0 (best) to 60 (worst) (15).

  • Includes heart disease, diabetes, cancer, or lung problems (e.g., asthma, emphysema, and chronic bronchitis).

  • #

    Includes stroke, myocardial infarction, or other thromboses.

  • **

    Includes bronchoscopy, biopsy, or hemoptysis.

  • ††

    Includes biopsy, dialysis, or transplant.

  • ‡‡

    Medical Outcomes Study (MOS) cognitive functioning scale (20), range 0 (worst) to 100 (best) (13).

  • §§

    Physical functioning subscale of the Short Form 36 (SF-36) (21), range 0 (worst) to 100 (best) (14).

  • ¶¶

    Proportion of the adult population in census block group that is employed.

Demographic characteristics
 Age, years
  18–3464 (17)27 (36)37 (12)
  35–54208 (55)36 (47)172 (57)
  55–64104 (28)13 (17)91 (30)
 Female359 (95)74 (97)285 (95)
 Ethnicity
  White249 (66)48 (63)201 (67)
  Hispanic29 (8)6 (8)23 (8)
  African American39 (10)4 (5)35 (12)
  Asian/Pacific Islander35 (9)13 (17)22 (7)
  Other24 (6)5 (7)19 (6)
 Marital status
  Never married84 (22)29 (38)55 (18)
  Married/partner227 (60)39 (51)188 (63)
  Widowed, separated, divorced65 (17)8 (11)57 (19)
 Education
  High school graduate or less96 (26)21 (28)75 (25)
  Some college173 (46)32 (42)141 (47)
  College graduate107 (28)23 (30)84 (28)
Health characteristics
 Disease severity
  Duration of SLE, years13.2 ± 8.3 (0–45)10.7 ± 6.7 (0–35)13.9 ± 8.5 (1–45)
  SLE activity (patient global assessment)5.0 ± 3.2 (0–10)4.1 ± 3.0 (0–10)5.3 ± 3.2 (0–10)
  CES-D§19.8 ± 13.1 (0–56)18.4 ± 13.1 (0–56)20.2 ± 13.2 (0–53)†
  ≥1 comorbid condition220 (59)33 (43)187 (62)
  Vascular events in past 5 years#85 (23)16 (21)69 (23)
  Lung manifestations in past 5 years**66 (18)7 (9)59 (20)
  Kidney manifestations in past 5 years††47 (13)14 (18)33 (11)
 Functional status
  MOS cognitive functioning scale‡‡51.8 ± 19.9 (6–83)55.4 ± 18.8 (8–83)50.9 ± 20.1 (6–83)†
  SF-36 physical functioning scale§§46.9 ± 29.9 (0–100)62.8 ± 29.0 (5–100)42.8 ± 28.9 (0–100)
 Area-level measures, %
  County employment rate7 ± 2 (3–12)7 ± 2 (3–10)7 ± 2 (3–12)†
  Neighborhood employment rate¶¶61 ± 12 (11–100)60 ± 13 (17–100)61 ± 12 (11–84)
Years since regular work4.1 ± 1.5 (1–6)3.2 ± 1.9 (1–6)4.3 ± 1.3 (1–6)

The enrollment and data collection protocol was approved by the University of California, San Francisco Committee on Human Research.

Statistical analysis.

Estimating time until work loss/entry.

We used the Kaplan-Meier method (20) to estimate the duration of time until work loss/entry among the employed and not employed samples, respectively. We then compared the employment patterns in the LOS sample with a general population sample using SIPP data. To match the SIPP and LOS samples, we dropped men from both samples because the LOS sample is primarily female (90%), and charted the first 3 years of followup for the LOS since the SIPP is a 36-month cohort. It was not possible to precisely match the timeframes for the 2 samples because the most recent SIPP cohort ended in 2004. However, the average unemployment rates were very similar for the years covered by the LOS and the SIPP (5.4% and 5.5%, respectively).

The analyses were stratified by age group. We used the Kaplan-Meier procedure in SUDAAN (Research Triangle Institute, Research Triangle Park, NC) to account for the SIPP sampling design.

Estimating risk factors for employment outcomes.

We used Cox proportional hazards regression models (21) to estimate risk factors for work loss/entry among the employed and not employed LOS samples, respectively. We estimated regressions on each of the 5 sets of covariates: demographic characteristics, neighborhood employment rate, disease severity, functional status, and for the work loss model, job characteristics. All variables in each set were included, unless there were problems with colinearity, in which case we selected the variable with the most explanatory power. We then combined sets of covariates in 2 full models, 1 containing all covariates except functional status and 1 containing all covariates except disease severity. Colinearity between the measures of disease severity and function precluded putting them in the same model. In the foregoing analysis, we found no main effect of work characteristics on the risk of work loss. Accordingly, we reran the full models excluding the work characteristics; because there was no change in the overall fit of the model, the latter model is not reported here. We also tried alternative measures of certain key risk factors; for example, substituting the Short Form 12 mental component score (22) for the CES-D. In no instance was there a compelling reason to report other than the principal analysis.

We used SAS statistical software, version 9.1 (SAS Institute, Cary, NC) Proc PHReg for the Cox proportional hazards regressions.

RESULTS

Tables 1 and 2 show the characteristics of those employed and not employed in the baseline year of the LOS, cross-classified by whether they subsequently left or entered work, respectively. Among the 394 persons with SLE employed at baseline, 92 (23.4%) left work over the ensuing 3 waves of data collection (Table 1). Those who left work did not differ significantly from those who did not in sex, ethnicity, marital status, or extent of education; they were, however, more likely to be ages 55–64 years. Persons with SLE who left work reported higher levels of SLE activity and CES-D scores (indicative of higher levels of depressive symptoms) and were more likely to report having ≥1 comorbid condition. They also reported slightly, albeit significantly, poorer cognitive status (by MOS scale) and poorer physical functioning (by SF-36 scale).

With the exception that persons with SLE who ultimately left work reported lower annual hours of employment in the baseline year (1,457 versus 1,707), they did not differ from those who remained at work on any other work characteristic. Notably, persons with SLE who left work did not live in counties with higher unemployment rates or in local neighborhoods (as measured by the Census block group) with lower employment rates.

Among the 376 persons with SLE who were not working at the time of the baseline interview, 76 (20.2%) entered work over the ensuing 3 waves of data collection (Table 2). Those who entered work were younger and less likely to be married, but did not differ in sex, ethnicity, or education. In terms of health characteristics, those entering work had shorter durations of disease, lower disease activity, fewer comorbid conditions, and fewer lung manifestations, but not thrombotic events or renal manifestations. Not surprisingly, they reported substantially better physical functioning at baseline. Although a significantly shorter amount of time had passed since they last worked, they did not differ from those who did not enter employment in their county unemployment rate or in their local neighborhood employment rate.

Figure 1 shows results of the time until work loss among those employed at baseline. Among persons with SLE of all working ages employed at baseline, >10% stopped working by 12 months after the baseline interview and ∼20% stopped working by 36 months. The percentage of individuals experiencing work loss was remarkably similar between persons with SLE of all working ages and the national sample from SIPP of persons who were these ages.

Figure 1.

Time until work loss among persons with systemic lupus erythematosus (Lupus Outcomes Study [LOS]) and a nationally representative sample (Survey of Income and Program Participation [SIPP]), by age. A, all ages, B, age 18–34 years, C, age 35–54 years, D, age 55–64 years.

Time until work loss was similar among persons with SLE and the SIPP sample for persons ages 35–54 years, the prime working ages, with ∼20% of each sample leaving work by 36 months. Among workers between ages 18 and 34 years, the LOS and SIPP samples had almost exactly the same probability of work loss until 12 months after the interview; after that point, however, persons with SLE did not sustain additional work loss in contrast to the SIPP sample.

Rates of work loss among persons with SLE who were between ages 55 and 64 years were similar to the SIPP national sample. At 36 months, ∼33% of both groups had stopped working.

Focusing just on those with SLE, the probability of work loss increased sharply at age ≥55 years. Approximately 20% of those between ages 18 and 54 years experienced work loss by 36 months, but >30% of those between ages 55 and 64 years did.

Figure 2 shows the results of the analysis of time until work entry among the 2 samples. Among persons of all working ages in the LOS, ∼10% had entered work by 12 months and ∼20% had entered work by 36 months. In the full SIPP sample, ∼25% had entered employment by 12 months and ∼40% had done so by 36 months. At that point, those with SLE were ∼50% as likely as those from the SIPP sample to have entered employment.

Figure 2.

Time until work entry among persons with systemic lupus erythematosus (Lupus Outcomes Study [LOS]) and a nationally representative sample (Survey of Income and Program Participation [SIPP]), by age.A, all ages, B, age 18–34 years, C, age 35–54 years, D, age 55–64 years.

The difference in rates of work entry between persons with SLE and the national sample was most pronounced among persons ages 35–54 years. In that age range, only ∼15% of persons with SLE and ∼20% from the SIPP had experienced work entry by 12 months after the initial interview. Among those between ages 18 and 34 years, job entry patterns were similar, and at 36 months, the rates were close to 45% and 55% for the LOS and SIPP samples, respectively. Very few of either group between ages 55 and 64 years experienced work entry; even at 36 months after the initial interview, only ∼10% of either group had experienced work entry.

Focusing just on those with SLE, the likelihood of work entry declined markedly after age 35 years. Approximately 45% of those between ages 18 and 34 years had entered work by 36 months, but only ∼15% of those ages 35–54 years and only ∼10% of those ages 55–64 years did so.

Table 3 shows the impact of various sets of risk factors for work loss individually and in combination among persons with SLE employed at the time of the baseline interview. With the exception of neighborhood employment rate and work characteristics, each set of risk factors was associated with the risk of work loss when analyzed alone. With respect to individual variables within sets, lower age, higher levels of cognitive and physical functioning, and higher levels of cognitive job demands were associated with a lower risk of work loss (the hazard ratio for cognitive and physical function is estimated per point on a 0–100 scale), whereas lower education and higher CES-D score (estimated per point on a 0–60 scale) were associated with a higher risk. When combining the sets in the full model with severity measures, only older age and higher CES-D score remained predictive of work loss. In the full model with functional measures, older age, never having been married, and lower cognitive and physical functioning were associated with work loss. None of the individual work characteristics was associated with work loss in the full models.

Table 3. Risk factors for work loss among participants employed at baseline*
VariableCox proportional hazards models
DemographicsArea levelDisease severityDisease functionWork characteristicsFull model 1: severityFull model 2: function
  • *

    Values are the hazard ratio (95% confidence interval) unless otherwise indicated. SLE = systemic lupus erythematosus.

  • P < 0.05.

  • Proportion of the adult population in census block group that is employed.

  • §

    Patient global rating of disease activity, range 0 (best) to 10 (worst).

  • Center for Epidemiologic Studies Depression Scale (CES-D) (19), range 0 (best) to 60 (worst) (15).

  • #

    Includes heart disease, diabetes, cancer, or lung problems (e.g., asthma, emphysema, and chronic bronchitis).

  • **

    Includes stroke, myocardial infarction, or other thromboses.

  • ††

    Includes bronchoscopy, biopsy, or hemoptysis.

  • ‡‡

    Includes biopsy, dialysis, or transplant.

  • §§

    Medical Outcomes Study (MOS) cognitive functioning scale (20), range 0 (worst) to 100 (best) (13).

  • ¶¶

    Physical functioning subscale of the Short Form 36 (SF-36) (21), range 0 (worst) to 100 (best) (14).

  • ##

    Full-time, full-year employment in a permanent position on a day shift for a single employer, not as a consultant (19).

  • ***

    From the Job Content Questionnaire, the conjoint presence of high levels of psychosocial job demands and low levels of control (17).

  • †††

    Includes walking; using stairs/inclines; sitting for long periods; stooping, crouching, or kneeling; lifting/carrying weights of 10 and/or 50 pounds; repeating the same hand motion ≥30 times/hour; bending over, twisting around; and using hand tools (17).

  • ‡‡‡

    Includes concentrating for long periods, interacting with other people, and using computers (18).

Age, years (55–64, reference)
 18–340.32 (0.16–0.65)    0.32 (0.15–0.66)0.37 (0.18–0.77)
 35–540.47 (0.29–0.76)    0.39 (0.22–0.66)0.45 (0.27–0.75)
Female1.21 (0.58–2.53)    1.11 (0.51–2.45)0.95 (0.42–2.13)
Nonwhite1.34 (0.87–2.07)    1.36 (0.85–2.20)1.50 (0.95–2.38)
Education (college graduate, reference)
 High school graduate or less1.91 (1.08–3.39)    1.59 (0.80–3.13)1.50 (0.77–2.92)
 Some college1.23 (0.78–1.93)    1.11 (0.67–1.85)1.14 (0.69–1.88)
Marital status (married, reference)
 Never married1.60 (0.94–2.73)    1.59 (0.91–2.76)1.79 (1.02–3.14)
 Widowed, separated, divorced0.91 (0.49–1.71)    0.81 (0.41–1.58)0.83 (0.43–1.62)
Neighborhood employment rate 0.72 (0.10–5.30)   1.01 (0.11–9.31)1.48 (0.16–13.65)
Disease duration, years  0.99 (0.96–1.02)  0.99 (0.96–1.02)0.99 (0.96–1.02)
SLE activity (patient global assessment)§  1.04 (0.96–1.13)  1.06 (0.98–1.15) 
CES-D  1.03 (1.01–1.05)  1.03 (1.01–1.05) 
≥1 comorbid condition#  1.33 (0.87–2.03)  1.24 (0.81–1.91) 
Vascular events in past 5 years**  0.99 (0.52–1.90)  0.90 (0.46–1.77) 
Lung manifestation in past 5 years††  1.56 (0.81–3.01)  1.64 (0.82–3.28) 
Kidney manifestations in past 5 years‡‡  1.13 (0.60–2.15)  1.12 (0.55–2.27) 
MOS cognitive functioning scale§§   0.98 (0.97–0.99)  0.98 (0.97–0.99)
SF-36 physical functioning scale¶¶   0.99 (0.98–1.00)  0.99 (0.98–1.00)
Traditional employment##    0.76 (0.49–1.19)0.74 (0.47–1.19)0.79 (0.49–1.25)
High job demands, low job control***    1.19 (0.68–2.06)0.84 (0.47–1.53)0.83 (0.46–1.51)
Sum of physical job demands†††    1.02 (0.95–1.10)1.03 (0.95–1.11)1.03 (0.95–1.12)
Sum of cognitive job demands‡‡‡    0.85 (0.72–1.00)0.93 (0.78–1.10)0.92 (0.78–1.09)
Occupation (professional/managerial, reference)
 Sales/technical/services    0.94 (0.53–1.66)0.84 (0.46–1.55)0.80 (0.44–1.47)
 Crafts/operative    0.67 (0.23–1.96)0.59 (0.19–1.86)0.52 (0.17–1.60)
 Administrative support/clerical    1.04 (0.61–1.77)0.73 (0.40–1.34)0.75 (0.41–1.36)
Industry (professional services, reference)
 Manufacturing/construction/extractive    1.56 (0.76–3.18)1.50 (0.69–3.26)1.57 (0.71–3.47)
 Miscellaneous industries    0.89 (0.53–1.49)0.91 (0.53–1.55)0.93 (0.54–1.60)
 Personal/business/repair    1.32 (0.69–2.52)1.06 (0.53–2.11)0.90 (0.45–1.80)
Chi-square model, df, P18.07, 8, 0.020.11, 1, 0.7425.79, 7, <0.00126.10, 2, <0.0018.84, 10, 0.5549.05, 26, 0.00448.31, 22, 0.001

Table 4 shows the results of the analysis of the various sets of factors affecting work entry individually and in combination. When analyzing the sets of factors separately, each set was significantly associated with the risk of work entry, with the exception of the neighborhood employment rate. With respect to individual variables, being in the youngest age group, never having been married, having a shorter duration of SLE, lower levels of disease activity, higher levels of physical functioning, and a shorter period of time since last regular employment were associated with an increased rate of work entry. In the multivariate analyses, age and marital status were not associated with the risk of work entry in either the severity or function models, whereas years since last regular work was associated with work entry in both models. Lower disease severity and fewer lung manifestations were associated with reduced risk of work entry in the severity model, whereas higher physical function was predictive of work entry in the function model.

Table 4. Risk factors for work entry*
VariableCox proportional hazards models
DemographicsArea levelDisease severityDisease functionWork characteristicsFull model 1: severityFull model 2: function
  • *

    Values are the hazard ratio (95% confidence interval) unless otherwise indicated. SLE = systemic lupus erythematosus.

  • P < 0.05.

  • Proportion of the adult population in census block group that is employed.

  • §

    Patient global rating of disease activity, range 0 (best) to 10 (worst).

  • Center for Epidemiologic Studies Depression Scale (CES-D) (19), range 0 (best) to 60 (worst) (15).

  • #

    Includes heart disease, diabetes, cancer, or lung problems (e.g., asthma, emphysema, and chronic bronchitis).

  • **

    Includes stroke, myocardial infarction, or other thromboses.

  • ††

    Includes bronchoscopy, biopsy, or hemoptysis.

  • ‡‡

    Includes biopsy, dialysis, or transplant.

  • §§

    Medical Outcomes Study (MOS) cognitive functioning scale (20), range 0 (worst) to 100 (best) (13).

  • ¶¶

    Physical functioning subscale of the Short Form 36 (SF-36) (21), range 0 (worst) to 100 (best) (14).

Age, years (55–64, reference)
 18–343.78 (1.80–7.97)    1.62 (0.67–3.91)1.24 (0.52–2.92)
 35–541.37 (0.72–2.61)    1.41 (0.71–2.78)1.18 (0.60–2.32)
Female2.53 (0.60–10.58)    2.14 (0.51–8.99)2.73 (0.65–11.46)
Nonwhite0.77 (0.45–1.32)    0.83 (0.49–1.41)0.89 (0.52–1.50)
Education (college graduate, reference)
 High school graduate or less0.92 (0.50–1.69)    1.22 (0.64–2.33)1.30 (0.68–2.47)
 Some college0.80 (0.46–1.38)    1.05 (0.59–1.87)1.07 (0.61–1.90)
Marital status (married, reference)
 Never married1.73 (1.01–2.95)    1.74 (0.98–3.08)1.71 (0.97–3.00)
 Widowed, separated, divorced0.86 (0.40–1.87)    1.02 (0.46–2.27)1.04 (0.47–2.28)
Neighborhood employment rate 0.61 (0.10–3.67)   0.56 (0.08–3.87)0.45 (0.06–3.33)
Disease duration, years  0.94 (0.91–0.97)  0.97 (0.93–1.00)0.97 (0.94–1.01)
SLE activity (patient global assessment)§  0.89 (0.82–0.97)  0.89 (0.82–0.98) 
CES-D  1.00 (0.98–1.02)  1.00 (0.98–1.02) 
≥1 comorbid condition#  0.63 (0.40–1.01)  0.81 (0.49–1.33) 
Vascular events in past 5 years**  0.90 (0.51–1.59)  0.75 (0.42–1.33) 
Lung manifestation in past 5 years††  0.51 (0.23–1.11)  0.45 (0.20–1.00) 
Kidney manifestations in past 5 years‡‡  1.51 (0.83–2.73)  0.94 (0.50–1.79) 
MOS cognitive functioning scale§§   1.00 (0.99–1.01)  0.99 (0.98–1.01)
SF-36 physical functioning scale¶¶   1.02 (1.01–1.03)  1.02 (1.01–1.03)
Years since regular work    0.66 (0.58–0.75)0.73 (0.62–0.85)0.75 (0.64–0.87)
Chi-square model, df, P30.01, 8, <0.0010.29, 1, 0.5934.42, 7, <0.00128.64, 2, <0.00124.25, 1, <0.00164.86, 17, <0.00167.53, 13, <0.001

DISCUSSION

It has been established that persons with SLE have substantially lower employment rates than individuals of similar age. Using the same data source as the present study, for example, we previously observed that by little more than a decade after onset, only approximately half of working-age adults with SLE were employed (3). The productivity of such adults had declined by approximately one-third, mostly as a result of complete cessation of work rather than reduced hours of those who remained on the job.

The estimates in the latter study as well as others, however, should be considered as conservative estimates of the impact of SLE on employment. All of the studies of employment among persons with SLE use retrospective data collection among prevalence cohorts because establishing true incidence cohorts is difficult in rare conditions such as this one. It stands to reason that, even though mortality rates in SLE have declined over the years, some persons with SLE died before becoming eligible to enter prevalence cohorts. Since such persons likely had severe forms of the condition, it is likely that had they not died, they would have had a high probability of work loss.

In most severe chronic diseases, the initial goal of improved treatment is to reduce mortality, in effect to turn fatal conditions into chronic ones. Thereafter, the goal shifts to improving quality of life. In SLE, the transition from a fatal to chronic condition is well underway (23, 24). The relatively low rates of employment would suggest that the transition to reducing the substantial impact of SLE on quality of life is incomplete.

The contribution of the present study is 2-fold. First, because it is prospective in design, we were able to capture the impact of a full range of risk factors on employment, including those subject to substantial recall bias such as past levels of disease activity. The study also included sets of risk factors not frequently included in work disability studies such as the unemployment rate in the county of the respondents and the employment rate of their neighborhoods. Second, it is known at this point that employment rates among persons with SLE are relatively low. The present study allows us to estimate the risk factors for transitions from current status that could result in improvement in the employment prospects of persons with SLE by decreasing rates of work loss and increasing rates of work entry.

As a result of transitions out of employment between the onset of SLE and the baseline year of the LOS, only approximately half were employed in the latter year. Over the ensuing 36 months, more than one-fifth of all of those who were employed in the baseline year experienced work loss. Time until work loss was similar for those ages 18–34 and 35–54 years. However, time until work loss was much shorter for persons with SLE ages 55–64 years, approximately 40% of whom had stopped working by 36 months after the initial LOS interview. With the caveat that persons with SLE started with lower employment rates, rates of work loss among all working-age persons were similar between those with SLE in the LOS and the national SIPP sample. However, the age patterns were different, with those persons ages 35–54 years in the national sample having the lowest rates of work loss, and those in the youngest and oldest age groups having higher rates.

Rates of work entry were substantially lower among persons with SLE than in the national sample. This was true in every age group, but the differential impact was especially profound among those ages 35–54 years, the ages when most of us are acquiring the jobs we will hold for the longest amount of time during our working lives, often called “career jobs” (25, 26). Together with the results for work loss, this suggests that persons with SLE take longer to gain the toehold in such jobs in the prime working ages, and then go on to sustain an earlier exit from employment, an effect accentuated by their initial relatively low employment rates.

Younger age and higher levels of cognitive functioning were associated with a lower risk of work loss among those employed, whereas higher levels of depressive symptoms were associated with a higher hazard ratio, suggesting that effective treatment for depression might reduce the speed with which persons with SLE exit the labor force. However, no single work characteristic predicted work loss, a finding at odds with many studies of patients with rheumatoid arthritis and other chronic conditions (27–30). The severity of SLE may simply trump risk factors found to affect work outcomes in these other conditions. The strongest factor affecting the risk of work entry was the amount of time that had elapsed since the last regular job, indicating once again the importance of maintaining employment as the key strategy to improving employment outcomes in SLE. How to accomplish the latter goal remains elusive, however, since we could not identify kinds of jobs or working conditions in the work loss models that were associated with the retention of employment.

The principal limitation of the current study is that the data source is not a true incidence cohort. As a result, when the cohort was formed, many of the LOS participants had already left work and could not be expected to report on the characteristics of their disease in prior years that had led them to stop working. This also limits our ability to study how individuals and their employers accommodate the onset of the disease and subsequent periods of severe exacerbation. It may also explain why there was no association between work characteristics and work loss; persons at highest risk of work loss may have left employment prior to the formation of the cohort. Another limitation is that self-report of disease variables may have limited our ability to estimate their impact on work loss, although we have validated respondent reports of disease manifestations (16).

Nevertheless, the results indicate that, at least until age 55 years, the employment problems of persons with SLE may be due more to their lower rates of job entry if they are out of the labor force than to high rates of work loss if they are employed. This result is broadly consistent with studies of other disease entities, in showing that every effort must be made to help persons with health problems, in this case SLE, stay on the job despite their illness (18). Unfortunately, the relative dearth of strong risk factors for work loss from this study suggests that figuring out how to accomplish this goal will not be easy.

AUTHOR CONTRIBUTIONS

Dr. Yelin had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study design. Yelin, Tonner, Katz, Criswell.

Acquisition of data. Yelin, Tonner, Criswell.

Analysis and interpretation of data. Yelin, Tonner, Panopalis, Yazdany, Criswell.

Manuscript preparation. Yelin, Tonner, Panopalis, Yazdany, Julian, Katz, Criswell.

Statistical analysis. Yelin, Tonner, Criswell.

Acknowledgements

The authors gratefully acknowledge the contributions of Janet Stein, Stephen King, Jessica Spry, and Rosemary Prem.

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