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. Author manuscript; available in PMC: 2014 Dec 6.
Published in final edited form as: J Occup Environ Med. 2013 Mar;55(3):318–324. doi: 10.1097/JOM.0b013e31827943c6

Clinically Significant Weight Gain One Year After Occupational Back Injury

Benjamin J Keeney 1, Deborah Fulton-Kehoe 2, Thomas M Wickizer 3, Judith A Turner 4, Kwun Chuen Gary Chan 5, Gary M Franklin 6
PMCID: PMC4258104  NIHMSID: NIHMS641697  PMID: 23247606

Abstract

Objective

To examine the incidence of clinically significant weight gain one year after occupational back injury, and risk factors for that gain.

Methods

A cohort of Washington State workers with wage-replacement benefits for back injuries completed baseline and 1-year follow-up telephone interviews. We obtained additional measures from claims and medical records.

Results

Among 1,263 workers, 174 (13.8%) reported clinically significant weight gain (≥7%) 1 year after occupational back injury. Women and workers who had >180 days on wage replacement at 1 year were twice as likely (adjusted OR=2.17, 95% CI=1.54–3.07; adjusted OR=2.40, 95% CI=1.63–3.53, respectively; both P<0.001) to have clinically significant weight gain.

Conclusions

Women and workers on wage replacement >180 days may be susceptible to clinically significant weight gain following occupational back injury.

Keywords: clinically significant weight gain, occupational injury, back injury, prospective study, worker's compensation

Introduction

The dangers of obesity to general health and specific diseases are well-known. Obesity is strongly associated with a shorter lifespan, lower quality of life, and higher rates of cardiovascular disease, various cancers, and type-II diabetes.1 In occupational settings, rates of back injury and increased workers’ compensation costs are also associated with obesity, as are overall rates of occupational injury, lower worker productivity, and reporting of non-injury back pain.2-5 Being overweight or obese is also associated with more workers’ compensation claims, more lost workdays, higher medical claims costs, and higher indemnity claims costs.4,6 Self-reported need for mental health services is associated with weight gain among injured workers.7 Although much is known about obesity's impact on back injuries and workers’ compensation, little is known about the extent of weight gain among injured workers or about the early predictors of weight gain.

We conducted an exploratory study, using a sample of workers with wage-replacement claims (at least one day of temporary total disability wage replacement) for work-related back injuries, to determine the incidence of clinically significant weight gain 1 year after occupational back injury. We expected that a subset of workers might gain a clinically significant amount of weight after injury (e.g., due to decreased physical activity and more time at home engaged in sedentary activities). If risk factors for such weight gain could be identified early after injury and before weight gain, preventive interventions might be developed. Therefore, a second objective of the study was to identify early predictors of clinically significant weight gain and develop an exploratory multivariate predictive model for weight gain. Finally, we explored the association of clinically significant weight gain with receipt of wage replacement (time-loss) benefits at 1 year after injury. We hypothesized that extended receipt of wage replacement benefits would be associated positively with weight gain. Based on previous research, we hypothesized that the following baseline variables would predict clinically significant weight gain 1 year after occupational back injury: higher baseline body mass index (BMI), greater injury severity, higher baseline pain and disability levels, lower work physical demands, greater worker fear-avoidance and worse mental health, lower education attainment, poor overall health status, an opioid prescription within 6 weeks after seeing a provider for the back injury, not using tobacco, and not returning to work by the baseline interview.1,3,4,7-10,12-24

Methods

Sample

We used the Washington State Workers’ Compensation Disability Risk Identification Study Cohort (D-RISC)9 data to examine the prevalence of overweight and obesity at the time of injury, the incidence of clinically significant weight gain in the year after injury, and early predictors of weight gain 1 year after occupational back injury. In D-RISC, potential risk factors for chronic disability were assessed in domains of interest that were used previously for occupational injury research.8-11 Eight domains (sociodemographic, employment-related, pain and function, clinical, health care, administrative/legal, health behavior, and psychological)8 were assessed in baseline telephone interviews with workers with recent back injuries.

D-RISC was a prospective, population-based study that recruited Washington State Workers Compensation State Fund workers from June 2002 through April 2004 with accepted and provisional claims for occupational back injuries. Weekly claims review identified workers who missed at least 4 days from work and received wage replacement benefits (temporary total disability). Approximately two-thirds of the non-federal Washington workforce is covered by the State Fund. The remaining third are covered by large, self-insured companies and were not included due to insufficient administrative data.

In D-RISC, from the claims database, 4,354 workers were identified. Of those, 1178 (27.1%) could not be contacted, 909 (20.9%) declined enrollment, and 120 (2.8%) were ineligible.9 The remaining 2,147 (49.3%) were enrolled in D-RISC and completed baseline interviews. Persons were later excluded from the analysis sample if they were not eligible for wage-replacement benefits in the first year after claim submission (n=240), were hospitalized for the injury (n=16), were missing information on age (n=3) or were not confirmed to have a back injury upon medical review (n=3).9 Hence, 1,885 (43.3%) were included in D-RISC. Of the 1,885, 1,319 participants completed the follow-up interview approximately 1 year after claim receipt and 1,269 (96.2%) participants reported their weight during both interviews.

Upon inspection of the data, 16 participants had very large weight changes after 1 year (≥ 50 lbs). From additional administrative records, we were able to obtain other data on weight for 3 of the 16 participants, and used these data in the analyses. We excluded 6 of the 16 participants from analysis due to inconsistencies between self-report and clinical data that could not be reconciled. The self-reported and clinical data of the remaining 7 participants, among the 16, were very similar and the original self-reported weights were retained in the data, creating a final analysis sample of 1,263 participants.

The analysis sample was slightly older [mean age (SD) 40.3 (11.1) vs. 37.5 (11.2) years, P < 0.001], had fewer workers of Hispanic ethnicity (14% vs. 21%, P = 0.008), was more educated (less than high school 11% vs. 19%, P < 0.001), was more likely to be married or living with a partner (68% vs. 57%, P < 0.001), and contained more workers with general health insurance (72% vs. 60%, P < 0.001), as compared to the 622 persons who did not complete the follow-up survey or were excluded due to problematic weight data.

Measures

Study participants completed structured telephone interviews at baseline and at 1 year. Workers were asked their current weight in both interviews. The baseline interview also asked for participant height, which was used to determine baseline BMI (weight in pounds divided by (height in inches2 x 703)).25 Baseline measures for the current study were a subset of those obtained in the larger study, with selection based upon prior research pertaining to occupational injury, BMI, and weight and weight change. Additional data were obtained from the Washington State Department of Labor and Industries (DLI) claims database, including the region of the worker's residence, the worker's type of industry, the specialty of the first provider seen for the injury, and the number of days between the injury and the first medical visit for the injury. Additionally, medical record review by trained occupational nurses, with substantial inter-rater reliability, was used to determine injury severity.11 (See Table 1 and the Appendix for more information about the measures.)

Table 1.

Baseline Variables Associated Bivariately (P < 0.10) with Clinically Significant Weight Gain (7%) One Year after Baseline Interview

Domain and variables No significant weight gain n=1089 (%) Significant weight gain n=174 (%) Odds ratio^ 95% CI P-value
Sociodemographic
Gender (ref=male) 775 (89.2) 94 (10.8) < 0.001
    Female 314 (79.7) 80 (20.3) 2.10 1.52 – 2.91
Employment-related
Fast pace (ref=strongly disagree/disagree) 277 (89.9) 31 (10.1) 0.09
    Agree 441 (86.5) 69 (13.5) 1.34 0.85 – 2.13
    Strongly agree 366 (83.2) 74 (16.8) 1.57 0.99 – 2.48
Returned to paid work by baseline interview (ref=Yes, same job) 365 (88.6) 47 (11.4) 0.02
    Yes, light duty or different job 293 (88.0) 40 (12.0) 1.02 0.65 – 1.61
    No 431 (83.2) 87 (16.8) 1.61 1.09 – 2.37
Pain and function
Pain interference with daily activities, past week (0=no interference, ref=0-3)40 379 (88.8) 48 (11.2) 0.04
    4 – 5 250 (88.3) 33 (11.7) 1.06 0.66 – 1.70
    6 – 7 188 (81.7) 42 (18.3) 1.75 1.11 – 2.76
    8 – 10 270 (84.6) 49 (15.4) 1.40 0.90 – 2.18
Clinical status
Current health aside from injury (ref=excellent) 219 (89.0) 27 (11.0) 0.01
    Very good 424 (88.1) 57 (11.9) 1.08 0.66 – 1.76
    Good 336 (84.4) 62 (15.6) 1.45 0.89 – 2.37
    Fair/poor 110 (80.3) 27 (19.7) 1.90 1.06 – 3.43
Health care
Specialty, first provider seen for injury ◇ (ref=primary care) 412 (88.2) 55 (11.8) 0.095
    Occupational medicine 60 (78.9) 16 (21.1) 2.06 1.10 – 3.87
    Chiropractor 302 (84.6) 55 (15.4) 1.46 0.97 – 2.20
    Other 315 (86.8) 48 (13.2) 1.19 0.78 – 1.82
Administrative/legal (No significant variables)
Health behavior (No significant variables)
Psychological
Catastrophizing ‡‡ (ref=0-1) 352 (89.1) 43 (10.9) 0.06
    Low (>1 – <2) 173 (85.2) 30 (14.8) 1.44 0.87 – 2.40
    Moderate (2 – <3) 334 (87.4) 48 (12.6) 1.13 0.72 – 1.76
    High (3 – 4) 230 (81.3) 53 (18.7) 1.78 1.14 – 2.78
Recovery expectations39 (0-10 scale, 10 = extremely certain will be working in 6 months, ref=10) 651 (88.8) 82 (11.2) 0.01
    High (7 – 9) 215 (83.3) 43 (16.7) 1.61 1.08 – 2.42
    Low (0 – 6) 198 (81.5) 45 (18.5) 1.84 1.23 – 2.76
SF-36 v2 Mental Health (ref=>50)39 449 (88.6) 58 (11.4) 0.07
    41 – 50 275 (87.3) 40 (12.7) 1.09 0.70 – 1.68
    ≤ 40 365 (82.8) 76 (17.2) 1.52 1.04 – 2.22
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All measures were obtained from worker baseline interviews unless stated otherwise

Missing, “don't know,” and refusal responses for each variable were combined into one response for each variable (results not shown)

Ref indicates reference group.

^

All odds ratios were adjusted for age and gender, except for gender

Score from the Short-Form-36 version 2 (SF-36v2) Mental Health scale; higher scores indicate better functioning39

◇

From worker's compensation database

‡‡

Mean of responses to three questions from the Pain Catastrophizing scale45

A weight gain at one year of at least 7% of baseline weight was used as a measure of clinically significant weight change.14, 16 – 18 Definitions of clinically significant weight change are not consistent in the literature. Weight changes of any,7 3%,27 and 5% have also been used,12, 13, 28 but we chose the more conservative measure of a 7% gain.

To test our hypothesis that weight gain was associated with receiving wage replacement benefits at one year after claim submission, we used a measure of wage replacement receipt obtained from administrative records that corresponded to a similar timeline as our weight change measure: whether or not workers were receiving wage replacement benefits 365 days after the date the claim was received by DLI. Additionally, we categorized the accumulated days on wage replacement by 1 year after claim receipt (1 – 29, 30 – 89, 90 – 179, 180+ days) to determine if there was a dose-response relationship with clinically significant weight gain.

Statistical Analyses

We first conducted bivariate logistic regression analyses to examine associations between baseline variables of interest in each domain and clinically significant weight change, adjusted by age and gender. Missing, “don't know,” and refusal responses for each variable were combined into one response and included in the analysis. Variables with the most missing data included time from the date of injury to the first medical visit (n=36), region of worker residence (35), paid bill for an opioid prescription within 6 weeks of the first medical visit for the injury (33), recovery expectations (29), source of blame for the injury (26), days of work missed due to non-back health problems in the previous year (23), days of work missed due to back problems in the previous year (18), worker self-report of whether his/her supervisor listens to work-related problems (17), worker self-report of whether the employer had offered job accommodations to allow him/her to work (16), worker self-report of number of previous worker's compensation claims (11), and worker self-report of change in pain since the injury (11).

Next, we created a multivariate logistic regression model predicting clinically significant weight gain (yes/no). We entered as independent variables all baseline variables with P-values < 0.10 in the bivariate analysis, along with age and gender. A standard 0.05 P-value for determining statistical significance of bivariate associations may exclude variables that might be significant in a multivariate model.29 Analyses were conducted with Stata Version 10.30

Results

Sample Characteristics

The sample of workers (N=1,263) was mostly non-Hispanic White (73%; 14% Hispanic; 14% other) and male (69%). At the baseline interview, 29.7% of the study participants were of normal weight (BMI < 25), 40.0% were overweight (25 ≤ BMI ≤ 30), and 30.3% were obese (BMI > 30). At one year, 174 (13.8%) participants self-reported weight that represented clinically significant (7%) weight gain from baseline and 103 (8.2%) participants gained more than 10% of their baseline weight. Sixty-two participants went from normal to overweight status, 66 went from overweight to obese, and 1 participant went from normal weight to obese, for a total of 129 (10.2%) participants with an increase in BMI category by 1 year.

Baseline predictors of weight gain in bivariate analyses

Table 1 shows the variables associated with clinically significant weight gain in the bivariate analyses. Six of 8 domains contained variables associated (P < 0.10) with weight gain. These included female gender (sociodemographics), having a fast-paced work environment prior to injury and not returning to work by the baseline interview (employment-related). The pain and function domain contained one predictor: activity interference due to pain was associated positively with weight gain. Worse current health, aside from injury, was the only predictor of weight gain in the clinical status domain. In the health care domain, weight gain was associated with the specialty of the first health care provider seen for the injury (occupational medicine specialist relative to primary care provider). Three variables were identified in the psychological domain: greater catastrophizing, poorer SF-3640 Mental Health scale scores, and lower recovery expectations for the back injury were associated with weight gain. No factors from the administrative/legal or health behavior domains were associated with weight gain. Variables that were not associated with weight gain are listed in the Appendix; these include baseline BMI, injury severity, physical demands at work, fear-avoidance, education, opioid prescription for the injury, and tobacco use status.

Multivariate model predicting weight gain

Table 2 shows results from the multivariate model that included age and the 9 variables that were associated (P < 0.10) bivariately with clinically significant weight gain. Gender was the only significant predictor of clinically significant weight gain. Women had approximately twice the odds of weight gain, as compared to men (adjusted OR = 2.17, 95% CI 1.54 – 3.07).

Table 2.

Multivariate Model Predicting Clinically Significant Weight Gain (7%) at One Year from Baseline Variables Associated Bivariately with Weight Gain

Baseline Predictor Adjusted OR^ 95% CI P-value
Age, yr (ref = 35 – 44) 0.14
    ≤ 24 1.12 0.60 – 2.08
    25 – 34 1.41 0.91 – 2.19
    45 – 54 0.96 0.61 – 1.51
    ≥ 55 0.59 0.29 – 1.21
Gender (ref=male) < 0.001
    Female 2.17 1.54 – 3.07
Fast pace (ref=strongly disagree /disagree) 0.40
    Agree 1.20 0.75 – 1.92
    Strongly agree 1.43 0.89 – 2.30
Return to paid work by baseline interview (ref=Yes, same job) 0.30
    Yes, light duty or different job 1.00 0.62 – 1.60
    No 1.35 0.87 – 2.10
Pain interference with daily activities, past week (0=no interference, ref=0-3)39 0.58
    4 – 5 0.92 0.55 – 1.53
    6 – 7 1.29 0.75 – 2.21
    8 – 10 0.93 0.53 – 1.64
Current health aside from injury (ref=excellent) 0.14
    Very good 1.12 0.67 – 1.85
    Good 1.45 0.87 – 2.40
    Fair/poor 1.86 1.00 – 3.45
Specialty, first provider seen for injury ◇ (ref=primary care) 0.15
    Occupational medicine 1.85 0.97 – 3.53
    Chiropractor 1.43 0.94 – 2.18
    Other 1.08 0.70 – 1.67
Catastrophizing ‡‡ (ref=0-1) 0.38
    Low (>1 – <2) 1.29 0.76 – 2.21
    Moderate (2 – <3) 0.92 0.56 – 1.51
    High (3 – 4) 1.29 0.76 – 2.22
Recovery expectations32 (0-10 scale, ref=10, 10 = extremely certain will be working in 6 month) 0.08
    High (7 – 9) 1.45 0.92 – 2.28
    Low (0 – 6) 1.53 1.00 – 2.33
SF-36 v2 Mental Health (ref=>50)39 0.86
    41 – 50 0.89 0.56 – 1.42
    ≤ 40 0.99 0.62 – 1.57
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^

Adjusted for all other variables in the multivariate model.

Each baseline variable included in this table was associated significantly (P < 0.10) in bivariate analyses with clinically significant weight gain by one year of initial occupational back injury.

Age was included as an adjusting variable.

Missing, “don't know,” and refusal responses for each variable were combined into one response for each variable (results not shown)

Ref indicates reference group.

Association of receiving wage replacement compensation with weight gain at one year

Receipt of wage replacement compensation at one year (189 of 1,263 participants) was associated with clinically significant weight gain after adjustment for age and gender (adjusted OR for receipt of wage replacement versus no wage replacement at one year = 2.24, 95% CI 1.51 – 3.33, P < 0.001; Table 3). Almost 25% of participants on wage replacement at 1 year after the injury had clinically significant weight gain, while 13.4% of those not receiving wage replacement compensation at 1 year gained significant weight. In the analysis examining categories of days on wage replacement, adjusting for age and gender, only wage replacement for more than 180 days was associated with clinically significant weight gain, compared to 1 – 29 days (adjusted OR 2.40, 95% 1.63 – 3.53, overall P < 0.001).

Table 3.

Associations of Clinically Significant Weight Gain (7%) at 1 Year and Wage Replacement Status by 1 Year after Occupational Back Injury, adjusted for age and gender

Wage Replacement Status # Persons (N=1,263) Adjusted OR 95% CI P-Values
At 1 Year No 1,070 <0.001
Yes 193 2.24 1.51 – 3.33
By 1 Year 1 – 29 days 754 <0.001
30 – 89 days 163 1.17 0.69 – 1.98
90 – 179 days 98 1.37 0.74 – 2.55
> 180 days 248 2.40 1.63 – 3.53
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Discussion

To our knowledge, this is the first prospective study to examine the incidence and predictors of clinically significant weight gain after an occupational injury. Almost 14% of participants reported weight gain at 1 year of at least 7% of baseline weight. Female gender was the only significant early predictor. Additionally, receiving wage-replacement benefits at 1 year was highly associated with clinically significant weight gain.

In this sample, accrued from 2002 – 2004, the baseline distribution of workers in different BMI categories (29.7% normal weight, 40.0% overweight, 30.3% obese) was fairly similar to that in the 2000 general U.S. population (35.5%, 34%, and 30.5%, respectively).31 The men in our sample had a slightly higher rate of obesity as compared to the national sample (29.7% versus 27.7%), whereas the women were less likely to be obese (31.5% versus 34.0%). The mean weight change of a 1.44 pound increase over 1 year in our sample was within the range of mean weight change in 1 year reported in previous studies of the American adult population (0.4 to 1.8 pound increases).27,32–37 In one study of a racially and socioeconomically diverse sample, fewer than 10% of participants gained more than 3% of their body weight in 1 year, compared to 14% of participants gaining more than 7% of their body weight in our sample of injured workers.27 In our data, men had an overall mean weight change of a 0.93 pound increase (SD 13.52) while women had a mean increase of 1.78 pounds (SD 14.4); these differences in overall weight change were not statistically significant (P = 0.31). One other study reported mean weight change separately by men and women over 1 year; those authors also found no statistical differences.27

Female gender was the only predictor of clinically significant weight gain. Other studies have noted that women in the United States have a higher prevalence of obesity, overweight, and weight gain compared to men.27,49,50 However, one study noted that adult women appear to be leveling off for overweight and obesity prevalence, while adult men are still increasing yearly.50 Of note, we were unable to discern pregnancy status in our data; one study noted that pregnancy status contributes to weight misreporting.51

Low recovery expectations (less certainty that he/she will be working in six months) at the baseline interview was associated significantly with clinically significant weight gain in bivariate analyses, but not statistically significant in the multivariate model. Low recovery expectations have been previously shown in this sample and in other studies to predict several outcomes of occupational back injury, including slower claim closure, slower end of payment benefits, and still being on disability leave after 6 months.10, 52 Recovery expectations may have been associated with weight gain in our study, at least in part, due to its association with being off work for a longer period of time, which we found to be strongly associated with weight gain.

Self-reported poor or fair health, apart from the back injury, was associated with weight gain in bivariate analyses, but not in the multivariate model. Worse self-reported health has been associated with high BMI scores and weight gain in multiple studies.53–55 Worse overall health may be associated with less physical activity, which may lead to weight gain.56 In addition, worse health may be associated with greater use of medications that may cause weight gain.53,57 These associations warrant study in further research.

Our work includes significant limitations. First, our outcome of weight gain is based upon two self-reported weights. Self-reported weight may not be accurate. However, in previous studies, participants appeared to misreport consistently, making multiple measures over time by an individual feasible to use in weight change research.51,58–61 Additionally, persons who are already overweight or obese may underreport their weight compared to persons of normal weight. 58,59 A model including age, gender, and pregnancy status has been suggested as a method to adjust for weight misreporting;51 age and gender were both included in our multivariate model. Another limitation is that our weight gain outcome is binary: whether the participant did or did not gain 7% of baseline body weight 1 year after occupational back injury. We did not assess weight trends among our sample in years prior to the injury. However, 7% weight gain is a marker for clinically significant weight change.14,16–18 Additionally, we were unable to include in our analysis some key known correlates of weight gain, such as diet, exercise, and social support status.62,63 We may also have sample selection bias; people who did not report their weight and thus were excluded from the study (n=50) may differ in important ways from those who reported their weight. If participants gained weight after the injury but before the baseline interview, we may be underestimating the proportion who gained clinically significant weight and thus underestimating some associations. Lastly, 30.0% of the D-RISC participants did not complete the 1-year follow-up interview, and we do not know whether results would have differed had weight at 1 year been available for the entire sample. We emphasize the exploratory nature of the analyses and the need to replicate findings in other samples.

This study has several strengths. These include a large, prospective, population-based sample in Washington State. We utilized different data sources (two telephone surveys, administrative data, and medical record review) for our variables among eight domains of interest. Our study is the first, to our knowledge, to explore variables associated with clinically significant weight gain in a cohort of workers with back injuries.

In sum, female workers with occupational back injuries were twice as likely as males to have clinically significant weight gain in the year after injury. In addition, receiving wage-replacement benefits 1 year after injury was associated with clinically significant weight gain. Approximately 10.8% of men and 20.3% of women in our sample gained a clinically significant amount of weight following an occupational back injury, possibly resulting in decreased quality of life, increased susceptibility to weight-influenced medical conditions, and increased medical costs. Factors influencing weight gain and obesity are multi-faceted and complex. Increasing our knowledge of weight gain may inform future interventions for preventing weight gain after occupational back injury.

Clinical Significance.

Fourteen percent of workers gained significant weight (≥7% of baseline weight) by one year after occupational back injury. Female gender and being on wage-replacement status for more than 6 months were highly associated with weight gain. Knowledge concerning risk factors for weight gain may inform future prevention strategies.

Acknowledgments

The manuscript submitted does not contain information about medical devices or drugs.

Source of Funding: Federal (CDCP/NIOSH) funds were received in support of this work via grant R01-OH04069. No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript.

Appendix

Appendix.

Non-Significant Bivariate Associations (P ≥ 0.10) of Baseline Variables with Clinically Significant Weight Gain (7%) by One Year after Initial Occupational Back Injury

Domain and variables No significant weight gain N=1089 Significant weight gain N=174 Odds ratio^ 95% CI P-value
Sociodemographic
Age, years (ref= 35-44 years) 339 53 0.14
    ≤24 years 94 17 1.16 0.64 – 2.09
    25 – 34 years 244 50 1.31 0.86 – 1.99
    45 – 54 years 289 43 0.95 0.62 – 1.47
    ≥ 55 years 123 11 0.57 0.29 – 1.13
Region of worker residence † (ref=urban) 633 97 0.64
    Suburban 184 33 1.17 0.75 – 1.80
    Large town 124 22 1.14 0.68 – 1.89
    Rural 115 20 1.12 0.66 – 1.90
Race/ethnicity (ref=White non-Hispanic) 798 122 0.34
    Hispanic 142 30 1.35 0.86 – 2.11
    Other 149 22 0.88 0.54 – 1.45
Education (ref=high school) 364 58 0.68
    Less than high school 120 14 0.73 0.39 – 1.36
    Vocational or some college 495 84 1.05 0.73 – 1.52
    College 110 18 1.00 0.56 – 1.78
Marital status (ref=married/living with partner) 748 114 0.78
    Other 340 60 1.05 0.74 – 1.48
Employment-related
Worker's industry ‡ (ref=trade/transportation) 285 39 0.57
    Natural resources 49 6 0.97 0.38 – 2.43
    Construction 201 27 1.11 0.65 – 1.89
    Manufacturing 83 8 0.75 0.34 – 1.68
    Management 192 26 0.96 0.56 – 1.64
    Education and health 155 36 1.25 0.73 – 2.14
    Hospitality 124 32 1.56 0.92 – 2.65
Heavy lifting (ref=not at all/rarely/occasionally) 510 83 0.42
    Frequently 363 51 0.90 0.61 – 1.32
    Constantly 215 39 1.19 0.78 – 1.83
Whole body vibration (ref=not at all/rarely) 708 127 0.46
    Occasionally/frequently 254 34 0.94 0.61 – 1.46
    Constantly 125 13 0.74 0.40 – 1.39
Physical demands (ref=sedentary/light) 211 43 0.49
    Medium 357 47 0.69 0.44 – 1.09
    Heavy 257 44 0.99 0.61 – 1.59
    Very heavy 258 39 0.85 0.52 – 1.40
Excessive amount of work (ref=strongly disagree/disagree) 871 134 0.21
    Strongly agree/agree 218 40 1.12 0.94 – 1.32
Enough time to do job (ref=Strongly agree/agree) 796 117 0.26
    Strongly disagree/disagree 293 57 1.22 0.86 – 1.73
Very hectic (ref=Strongly disagree/disagree) 313 39 0.60
    Agree 494 85 1.30 0.86 – 1.96
    Strongly agree 279 49 1.12 0.70 – 1.78
Supervisor listens to my work problems (ref=agree) 622 101 0.25
    Strongly disagree/disagree 205 40 1.03 0.69 – 1.56
    Strongly agree 248 30 0.67 0.43 – 1.04
Satisfaction with job (ref=Somewhat or very satisfied) 944 149 0.30
    Not at all or not too satisfied 142 25 1.02 0.64 – 1.64
Co-worker relations (0 – 10 scale, ref=10, get along extremely well) 570 90 0.87
    8 – 9 394 67 1.07 0.75 – 1.51
    0 – 7 121 16 0.86 0.48 – 1.53
Job type at time of injury (ref=full-time) 992 158 0.26
    Part-time 97 15 0.71 0.39 – 1.29
Seasonal job at injury (ref=no) 1020 167 0.35
    Yes 68 7 0.68 0.30 – 1.52
Temporary job at injury (ref=no) 1024 163 0.55
    Yes 62 11 1.23 0.63 – 2.41
Job duration ≥ 6 months 865 135 0.67
    < 6 months 222 39 1.09 0.73 – 1.62
Employer offered job accommodation (ref=Yes) 517 75 0.15
    No 561 94 1.28 0.92 – 1.79
Pain and function
Number pain sites (ref=0-2 sites) 528 70 0.21
    3 – 4 sites 403 74 1.37 0.96 – 1.97
    5 – 8 sites 158 30 1.29 0.80 – 2.09
Pain intensity, past week (0= no pain, ref= 0–3)40 291 41 0.79
    4 – 5 289 43 0.99 0.62 – 1.58
    6 – 7 286 48 1.07 0.68 – 1.68
    8 – 10 223 42 1.24 0.77 – 1.99
Pain interference with work, past week (0=no interference, ref=0-3)40 405 52 0.32
    4 – 5 189 29 1.20 0.74 – 1.97
    6 – 7 192 33 1.35 0.84 – 2.18
    8 – 10 300 59 1.52 1.00 – 2.29
Roland questionnaire € (0=no disability) (ref=0-8)42 326 47 0.23
    9 – 16 386 53 0.95 0.62 – 1.45
    17 – 24 377 74 1.30 0.87 – 1.95
SF-36 v2 Physical Function (ref=>50)39 276 39 0.26
    41 – 50 209 27 0.93 0.55 – 1.57
    30 – 40 279 42 1.03 0.64 – 1.66
    < 30 325 66 1.40 0.90 – 2.18
SF-36 v2 Role Physical (ref=>50)39 239 37 0.11
    30 – 50 469 63 0.82 0.53 – 1.28
    < 30 381 74 1.22 0.79 – 1.90
Pain change since injury (ref=better) 762 111 0.49
    Same 198 42 1.36 0.92 – 2.02
    Worse 120 19 1.00 0.59 – 1.71
Clinical status
Injury severity †† (ref=mild strain/sprain)11 594 91 0.31
    Major strain/sprain with substantial immobility but no evidence of radiculopathy 215 36 1.07 0.70 – 1.63
    Evidence of radiculopathy or abnormalities 273 47 1.15 0.78 – 1.70
Pain radiates below knee (ref=no) 791 119 0.27
    Yes 298 55 1.22 0.86 – 1.74
Previous similar back injury (ref=no) 568 101 0.73
    Yes 521 73 0.94 0.67 – 1.32
Previous injury (any type) with ≥ 1 month off work (ref=no) 791 128 0.49
    Yes 295 46 1.14 0.78 – 1.67
Number of self-reported worker's compensation claims before current injury (ref=0) 402 64 0.40
    1 328 49 1.06 0.70 – 1.60
    2 – 3 236 40 1.31 0.84 – 2.04
    ≥ 4 115 18 1.33 0.74 – 2.39
Work days missed because of back, previous year (ref=0) 720 114 0.34
    1 – 10 269 39 0.92 0.62 – 1.37
    > 10 87 16 1.31 0.73 – 2.33
Work days missed because of other health problems, previous year (ref=0) 458 56 0.20
    1 – 10 536 98 1.34 0.94 – 1.91
    > 10 78 14 1.26 0.66 – 2.40
Number other major medical problems (ref=0) 906 147 0.99
    ≥ 1 182 27 1.00 0.63 – 1.60
General health, year prior to injury (ref=excellent) 262 33 0.23
    Very good 415 62 1.16 0.74 – 1.83
    Good 320 58 1.39 0.88 – 2.21
    Fair/poor 90 21 1.71 0.93 – 3.13
Opioid Rx within 6 weeks of injury (ref=no) 703 109 0.64
    Yes 359 59 1.07 0.76 – 1.52
Health care
Health care provider recommended exercise (ref=yes) 768 126 0.66
    No 319 48 0.92 0.64 – 1.33
Health insurance (ref=yes) 787 119 0.32
    No 301 54 1.13 0.79 – 1.62
Administrative/legal
Time from injury to first medical visit for injury ◇ (ref=0-6 days) 845 123 0.12
    7 – 13 days 119 26 1.66 1.03 – 2.66
    ≥ 14 days 96 18 1.33 0.77 – 2.30
Health behavior
Tobacco use (ref=no) 591 92 0.63
    Occasionally/frequently 166 23 0.90 0.55 – 1.48
    Daily 332 59 1.14 0.80 – 1.63
Alcohol Use Disorder Identification Test-Consumption (AUDIT-C)^^ (ref=negative, AUDIT-C score of 0 – 3 for males, 0 – 2 for females)41 755 129 0.30
    Positive (4 – 12 for males, 3 – 12 for females) 331 44 0.77 0.53 – 1.12
Baseline Body Mass Index (BMI) (ref=<25) 318 57 0.89
    25 – 29 (overweight) 443 63 0.92 0.62 – 1.37
    ≥ 30 (obese) 328 54 1.00 0.67 – 1.51
Psychological
Blame for injury39 (ref=work) 527 91 0.41
    Self 230 27 0.72 0.45 – 1.14
    Someone/something else 151 30 1.11 0.70 – 1.75
    Nothing/no one 160 21 0.80 0.48 – 1.33
Work fear-avoidance (ref= <3, very low)◇◇ 214 28 0.31
    Low-moderate (>3 – <5) 358 51 1.11 0.68 – 1.82
    High (5 – 6) 517 95 1.37 0.87 – 2.15
Open in a new tab

Missing, “don't know,” and refusal responses for each variable were combined into one response for each variable (results not shown)

Ref indicates reference group.

All measures were obtained from worker baseline interviews except where noted

^

All odds ratios were adjusted for age and gender, except for age

†

By residential zip code, using the Washington State guidelines classifications at http://www.doh.wa.gov/Data/Guidelines/RuralUrban

‡

Derived from Standard Industrial Codes (SIC)

€

Roland-Morris Disability Questionnaire assesses overall back disability42-44

Scores from the Short-Form-36 version 2 (SF-36v2) Physical Function and Role Physical scales; higher scores indicate better functioning39

††

Rated by trained nurses based on medical records early in the claim

◇

From worker's compensation database

^^

The AUDIT-C score is a screening test for problematic alcohol usage41

◇◇

Mean of responses to two questions from the Fear-Avoidance Beliefs Questionnaire work scale46

Footnotes

Dr. Keeney was a doctoral candidate in the Department of Health Services in the School of Public Health at the University of Washington when this research was conducted. He is now a Post-Doctoral Fellow in the Department of Orthopaedics at Dartmouth Medical School.

The manuscript submitted does not contain information about medical devices or drugs.

Conflicts of Interest:

No conflicts of interest were declared.

Contributor Information

Benjamin J. Keeney, Department of Orthopaedics, Dartmouth Medical School, Dartmouth College.

Deborah Fulton-Kehoe, Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington.

Thomas M. Wickizer, Division of Health Services Management and Policy, College of Public Health, Ohio State University.

Judith A. Turner, Departments of Psychiatry & Behavioral Sciences and Rehabilitation Medicine, School of Medicine, University of Washington.

Kwun Chuen Gary Chan, Departments of Biostatistics and Health Services, School of Public Health, University of Washington.

Gary M. Franklin, Washington State Department of Labor and Industries, Olympia, WA Departments of Environmental & Occupational Health Sciences and Health Services, School of Public Health, University of Washington Department of Neurology, School of Medicine, University of Washington.

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