Work Productivity Loss and Health-Related Quality of Life in People Living with Atopic Dermatitis: A Canada-Wide Cross-Sectional Study

Abstract

Abstract: Background: As new therapies for atopic dermatitis (AD) are developed, it is increasingly important to assess how AD impacts patient-reported outcomes.

Objective: To quantify productivity loss, work impairment, and health-related quality of life (HRQOL) among individuals with different levels of AD severity.

Methods: Employed adults from across Canada with a history of AD completed a web-based questionnaire. AD severity was assessed using the Patient-Oriented Eczema Measure; productivity loss, work impairment, and HRQOL were evaluated by the Valuation of Lost Productivity, Work Productivity and Activity Impairment, and Veterans RAND 12-item Health Survey (VR-12) questionnaires, respectively. The association between outcomes and AD severity was evaluated using multiple linear regression.

Results: Among the 200 participants, productivity loss increased with AD severity, but this was not statistically significant. Work impairment was greater in those with moderate (adjusted difference 13.6%[95% CI: 3.0, 24.1]) and severe to very severe AD (adjusted difference 20.5%[95% CI: 8.3, 32.7]) compared to those with no or mild AD. VR-12 health utility was lower for individuals with moderate (adjusted difference −0.08[95% CI: −0.16, −0.01]) and severe to very severe AD (adjusted difference −0.17[95% CI: −0.26, −0.08]) compared to those with mild or no AD.

Conclusions: Greater AD severity was associated with greater work impairment and worse HRQOL.

Capsule Summary

Among employed adults living with atopic dermatitis (AD) in Canada, AD severity (as measured using the Patient Oriented Eczema Measure questionnaire) was associated with greater work and activity impairment and lower health utility (as measured using the Veterans RAND 12-item Health Survey).

These findings provide further quantification that AD can impact productivity and health-related quality of life.

These data will be useful for future health economic analyses as new treatments for AD come to market.

INTRODUCTION

Atopic dermatitis (AD) is a common, chronic inflammatory skin disease that manifests with pruritus (itching), xerosis (dry skin), and minimally scaly erythematous plaques.¹ People affected by AD are at increased risk of developing atopy (eg, food allergies, asthma, allergic rhinitis, contact dermatitis, and hand dermatitis) and non-atopic comorbidities (eg, viral and bacterial skin infections, mood disorders, and autoimmune disorders).² AD is prevalent in all age groups of adults and is responsible for a significant proportion of the worldwide burden of skin disease.^3,4 The clinical manifestations of AD and associated comorbid conditions can substantially affect health-related quality of life (HRQOL),^{5B6 -14} and, in turn, can impact productivity at work.^14,15

Work productivity loss measurements and health utility assessments of HRQOL have emerged as important patient-reported outcomes in AD.^{14B15 -19} These outcomes have been used to assess the efficacy of AD treatments and can be incorporated into cost-effectiveness analyses.^16,19,20 Due to the emergence of a variety of treatment options for AD and increasingly limited healthcare budgets, it has become important to quantify how disease severity impacts these outcomes.

A few observational studies have examined the impact of AD on work productivity loss and HRQOL.^14,15,17,18 However, collecting additional data from patients in different settings and using different outcome measures should be prioritized. Thus far, the Work Productivity and Activity Impairment Questionnaire (WPAI) has been used to measure work productivity loss in AD.^14-16 Although widely used, the WPAI may not be the most economically accurate or comprehensive instrument as it does not directly quantify productivity loss in hours or measure unpaid productivity losses (such as loss from childcare or housework).²¹ Similarly, virtually all health utility estimates of HRQOL in AD have used the EuroQol-5 dimensions (EQ-5D) instrument.^10,17,18,22 Other health utility measures that more comprehensively capture mental health impacts [eg, the Veterans RAND 12-item Health Survey (VR-12)] may be preferable.²³ Additionally, most studies examining work productivity loss and health utility in AD have been conducted in the United States or Europe;^{14,15,17,18,24} further research in other countries is needed to validate these findings.

Comprehensive, patient-centered data that address these knowledge gaps would be valuable in further understanding the impact of AD and would facilitate health economic analyses. To this end, the objective of this study was to evaluate productivity loss and HRQOL in individuals with varying levels of AD severity in a national cross-sectional study in Canada.

METHODS

Study Design and Participants

This was a cross-sectional study in which participants completed an online questionnaire administered using Qualtrics® (Provo, Utah). Participants were recruited from across Canada through the Ipsos iSay market research platform. Eligibility criteria included ≥19 years of age, a diagnosis of atopic dermatitis, currently employed, Canadian residency, and an ability to comprehend English or French. Participants completed screening questions on the Ipsos platform, and those eligible were directed to the study questionnaire on Qualtrics®. As part of the Ipsos iSay platform, participants receive rewards for completing surveys, but cannot complete a survey more than once.

This study was part of a larger project that also examined patient-reported outcomes in migraine and alopecia areata.^25,26 The study was developed in collaboration with a patient partner living with AD, one with migraine, and one with alopecia areata. A draft of the questionnaire was piloted in three individuals with a history of AD, three individuals with migraine, and one individual with alopecia areata. Questions related to demographics and productivity loss were the same for the three diseases. The questions related to disease history, severity, and treatment were disease-specific. After they completed the draft questionnaire, participants were interviewed for feedback, and appropriate revisions were made. The final questionnaire was available to study participants in English and French.

This study was approved by the University of British Columbia Research Ethics Board (REB# H22-03211). Recruitment for this study occurred between January 15 and February 12, 2024. Participants provided consent electronically before initiating the questionnaire. We followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting observational studies.

Atopic Dermatitis Severity

The severity of AD was evaluated using the Patient-Oriented Eczema Measure (POEM).²⁷ The POEM is widely used in both clinical and research settings and is recommended by the Harmonising Outcome Measures for Eczema initiative as the core outcome instrument for measuring patient-reported symptoms in AD trials.²⁸ The POEM consists of 7 items asking respondents about the number of days affected by specific eczema symptoms in the last week. For each item, there are five response options ranging from “no days” (scored as 0 points) to “every day” (scored as 4 points). The maximum total score is 28 points. Based on the POEM score, we categorized participants as having no to mild AD severity (0–7 points), moderate severity (8–16 points), and severe to very severe (17–28 points).

Outcomes

The primary measure of productivity loss was measured using the Valuation of Lost Productivity (VOLP) questionnaire.²⁹ The VOLP consists of questions that inquire about absenteeism (number of absent workdays due to health), presenteeism (hours actually taken to complete all work relative to the hours taken to complete the same work if not experiencing any health problems), and unpaid work loss (hours of paid and unpaid help received for unpaid work activities due to health).²⁹ It has been validated and used in other chronic conditions to generate estimates for health-related productivity loss in hours over the preceding 3 months.^{29B30 -33} The estimated hours of productivity loss can then be converted to monetary terms by multiplying by the hourly wage.

In this study, the primary outcome was total hours of productivity loss, calculated as the sum of paid productivity loss (from absenteeism and presenteeism) and unpaid productivity loss. The hours of total paid productivity loss, hours lost due to absenteeism, hours lost due to presenteeism, and hours of unpaid productivity loss were evaluated as secondary outcomes. Our prior studies have described details regarding calculating the productivity loss outcomes using the VOLP.^26,34

A secondary measure of productivity loss was the work and activity impairment percentage measured by the WPAI- General Health questionnaire. The WPAI is a validated measure that assesses the impact of health on work productivity and impairment of regular activities in the prior week.^35,36

HRQOL was measured by the VR-12. The VR-12 was developed from the Veterans RAND 36-item Health Survey and modified from the original RAND version of the 36-item Health Survey version 1.0 (also known as the MOS SF-36). The VR-12 is a generic HRQOL instrument that includes 14 items. The first 12 correspond to 8 health domains (general health, physical functioning, role physical, bodily pain, role emotional, vitality, mental health, social functioning), while the remaining two questions capture changes in physical and emotional health over the past year.^37,38 We used Canadian preference weights to derive a health utility score (0 represents death and 1 represents best possible health) from VR-12 responses.³⁹

Statistical Analysis

Mean values for each outcome were calculated for different levels of AD severity based on POEM responses. We then used ordinary least squares (OLS) regressions to measure the association between AD severity level and the outcomes while adjusting for potential confounding variables. These additional covariates were prespecified and captured from questionnaire responses. These included age, gender, ethnicity, marital status, education level, work income, household income, employment status (part of VOLP), work habits, and comorbidities. We chose to use OLS models for productivity loss outcomes based on previously published practical recommendations for regression model selection in productivity loss analyses.⁴⁰

Statistical tests were two-sided, and the threshold for significance was P < 0.05. Analyses were performed using R statistical software version 4.3.3 and Stata version 15.1 (StataCorp LLC, College Station, TX).

RESULTS

200 individuals with a history of AD had complete responses and were included in the analyses. The characteristics of the study population are described in Table 1. The mean (standard deviation [SD]) age was 37.1 (10.2) years; 63.5% were women, 69.0% were White, 73.0% worked full time, and 48.5% were sedentary at work. Regarding disease severity, 23.0% had no to mild AD, 51.5% had moderately severe AD, and 25.5% had severe to very severe AD.

Table 1.

Characteristics of the Study Population

Characteristic	No to Mild (POEM 0–7)	Moderate (POEM 8–16)	Severe to Very Severe (POEM 17–28)	AllN (%)
Total, row %	46 (23.0%)	103 (51.5%)	51 (25.5%)	200 (100%)
Sex
Man	13 (28.3%)	41 (39.8%)	19 (37.3%)	73 (36.5%)
Woman	33 (71.7%)	62 (60.2%)	32 (62.7%)	127 (63.5%)
Age, mean (SD)	38.1 (11.2)	35.6 (9.1)	39.0 (11.1)	37.1 (10.2)
Race/ethnicity
Other race/ethnicity^a	20 (43.5%)	32 (31.1%)	10 (19.6%)	62 (31.0%)
White	26 (56.5%)	71 (68.9%)	41 (80.4%)	138 (69.0%)
Marital status
Not married or common-law	29 (63.0%)	36 (35.0%)	21 (41.2%)	86 (43.0%)
Married or common-law	17 (37.0%)	67 (65.0%)	30 (58.8%)	114 (57.0%)
Education
No university or college education	21 (45.7%)	59 (57.3%)	29 (56.9%)	109 (54.5%)
University or college education	25 (54.3%)	44 (42.7%)	22 (43.1%)	91 (45.5%)
Work income
<$50,000	13 (28.3%)	25 (24.3%)	17 (33.3%)	55 (27.5%)
$50,000–$99,999	25 (54.3%)	45 (43.7%)	16 (31.4%)	86 (43.0%)
≥$100,000	5 (10.9%)	30 (29.1%)	16 (31.4%)	51 (25.5%)
Household income
<$50,000	8 (17.4%)	17 (16.5%)	10 (19.6%)	35 (17.5%)
$50,000–$99,999	26 (56.5%)	36 (35.0%)	17 (33.3%)	79 (39.5%)
$100,000–$149,999	7 (15.2%)	24 (23.3%)	10 (19.6%)	41 (20.5%)
≥$150,000	3 (6.5%)	24 (23.3%)	12 (23.5%)	39 (19.5%)
Number of comorbidities^b
0	21 (45.7%)	37 (35.9%)	8 (15.7%)	66 (33.0%)
1	13 (28.3%)	25 (24.3%)	11 (21.6%)	49 (24.5%)
≥2	12 (26.1%)	41 (39.8%)	32 (62.7%)	85 (42.5%)
Employment status
Working full-time	35 (76.1%)	77 (74.8%)	34 (66.7%)	146 (73.0%)
Working part-time, self-employed, or other	11 (23.9%)	26 (25.2%)	17 (33.3%)	54 (27.0%)
Workdays per week, mean (SD)	4.7 (1.1)	4.8 (1.0)	4.7 (1.3)	4.7 (1.1)
Work hours per week, mean (SD)	37.2 (22.1)	33.4 (14.3)	28.0 (14.8)	32.9 (16.7)
Work habits
Sedentary at work	21 (45.7%)	56 (54.4%)	20 (39.2%)	97 (48.5%)
Mildly active at work	17 (37.0%)	34 (33.0%)	21 (41.2%)	72 (36.0%)
Moderate to strenuous activity at work	8 (17.4%)	13 (12.6%)	10 (19.6%)	31 (15.5%)
Work from home
No work from home	20 (43.5%)	44 (42.7%)	18 (35.3%)	82 (41.0%)
Work from home at least part of the time	26 (56.5%)	59 (57.3%)	33 (64.7%)	118 (59.0%)

This table is structured similarly to our previous study.²⁶ All percentages represent column proportions unless otherwise indicated.

Other race/ethnicity includes South Asian (eg, East Indian, Pakistani, Sri Lankan, etc.), Chinese, First Nations, Southeast Asian (eg, Vietnamese, Cambodian, Malaysian, Laotian, etc.), West Asian, Filipino, Latin American, Métis, Korean, Japanese, Arab, Inuit, Black, Indigenous/Aboriginal (not included elsewhere), Other, and mixed (i.e., more than one) ethnicities.

Comorbidities include asthma, arthritis or osteoporosis, back problems, cancer, cardiovascular disease, chronic obstructive pulmonary disease (COPD), diabetes, mental health conditions, neurological conditions, digestive diseases, fibromyalgia or chronic fatigue syndrome, kidney disease, liver disease or gallbladder problems, other.

POEM, Patient-oriented Eczema Measure; SD, standard deviation.

Supplementary Table S1 shows the AD treatment strategies and workplace supports reported by participants. The most commonly used strategies to treat or prevent AD were topical medications (87.0%), followed by vitamin supplements (47.5%) and lifestyle changes (46.0%). Regarding the workplace supports provided, 36.0% had been granted paid leave, 26.5% flexible work arrangements, and 25.5% unpaid leave.

As measured by the VOLP questionnaire, the mean [SD] hours of total productivity loss in the past 3 months were higher in participants with moderately severe AD (131.9 [221.5] hours) and severe to very severe AD (132.5 [200.1] hours) compared to no to mild AD (72.7 [114.6] hours) (Table 2). Specifically, the mean [SD] paid productivity loss (including absenteeism and presenteeism) was higher in those with moderately severe AD (67.2 [101.1] hours) and severe to very severe AD (61.2 [91.4] hours) than those with no to mild AD (49.2 [63.5] hours). The mean [SD] hours of unpaid productivity loss also increased with AD severity (35.9 [114.8] for no to mild AD, 60.3 [148.3] for moderately severe AD, and 73.7 [191.6] for severe to very severe AD).

Table 2.

Productivity Loss and Percentage Impairment by Atoptic Dermatitis Severity Level

Outcomes	No to Mild (POEM 0–7)Mean (SD)N = 46	Moderate (POEM 8–16)Mean (SD)N = 103	Severe to Very Severe (POEM 17–28)Mean (SD)N = 51	AllN = 200	P value*
VOLP (last 3 months)
Total work productivity loss, hours^a	72.6 (114.6)	131.9 (221.5)	132.5 (200.1)	118.9 (197.3)	0.236
Paid work productivity loss, hours^a	49.2 (63.5)	67.2 (101.1)	61.2 (91.4)	61.6 (91.2)	0.576
Absenteeism loss, hours	17.6 (37.3)	33.4 (65.2)	29.0 (70.7)	28.6 (61.5)	0.351
Presenteeism loss, hours^a	31.9 (49.7)	32.9 (73.2)	31.7 (56.2)	32.4 (63.9)	0.992
Unpaid work productivity loss, hours	35.9 (114.8)	60.3 (148.3)	73.7 (191.6)	58.1 (153.8)	0.474
WPAI (last 7 days)
Percent overall work impairment^b	32.7 (25.4)	51.2 (30.0)	56.4 (28.6)	48.3 (29.8)	<0.001
Percent activity impairment	30.4 (23.4)	47.0 (27.0)	55.2 (24.2)	45.3 (26.9)	<0.001
VR-12 (last 4 weeks)
Health utility	0.68 (0.15)	0.55 (0.23)	0.45 (0.25)	0.56 (0.23)	<0.001

This table is structured similarly to our previous study.²⁶

Sample size N = 185, and 15 participants did not provide valid responses for presenteeism questions.

Sample size N = 188, and 5 participants had valid question skip patterns [not currently employed (working for pay), or 0 hours missed because of health problems and 0 hours worked in the past 7 days] and 7 participants did not provide a valid response for actual work hours in the past 7 days.

*Global p-values are based on F-test statistics calculated from one-way Analysis of Variance.

POEM, Patient-oriented Eczema Measure; SD, standard deviation; VOLP, Valuation of Lost Productivity; WPAI, Work Productivity and Activity Impairment.

The mean [SD] WPAI percent overall work impairment (over the past 7 days) reported by participants also increased with AD severity (32.7 [25.4]% for no to mild AD, 51.2 [30.0]% for moderately severe AD, and 56.4 [28.6]% for severe to very severe AD), as did percent activity impairment (30.4 [23.4]%, 47.0 [27.0]%, and 55.2 [24.2]%, respectively) (Table 2).

The mean (SD) VR-12 health utility (HRQOL over the past 4 weeks) decreased with AD severity (0.68 [0.15] for no to mild AD, 0.55 [0.23] for moderately severe AD, and 0.45 [0.25] for severe to very severe AD) (Table 2).

In our multiple regression models, compared to those with mild AD, those with moderate AD reported greater productivity loss as measured by the VOLP (adjusted difference 49.5 hours; 95% CI: −28.9 to 127.9) (Table 3 and Supplementary Table S2). Similar results were observed for those with severe to very severe disease (adjusted difference 52.5 hours, 95% CI: 36.6–141.6). These differences were not statistically significant.

Table 3.

Multiple Regression Models for Hours of Productivity Loss and Health-Related Quality of Life

	No to Mild (POEM 0–7)	Moderate (POEM 8–16)Coefficient (95% CI)	Severe to Very Severe (POEM 17–28)Coefficient (95% CI)
VOLP (last 3 months)
Total productivity loss hours	[Reference]	49.5 (−28.9,127.9)	52.5 (−36.6,141.6)
Paid productivity loss hours	[Reference]	14.6 (−20.5,49.6)	0.7 (−39.2,40.6)
Unpaid productivity loss hours	[Reference]	22.2 (−34.7,79.1)	45.7 (−20.8,112.1)
WPAI (last 7 days)
Percent overall work impairment	[Reference]	13.6 (3.0,24.1)*	20.5 (8.3,32.7)**
Percent activity impairment	[Reference]	12.2 (3.0,21.5)*	19.2 (8.3,30.0)***
VR-12 (last 4 weeks)
Health utility	[Reference]	−0.08 (−0.16,−0.01)*	−0.17 (−0.26,−0.08)***

Models are adjusted for gender, age, ethnicity, marital status, education, employment status, work habits, and the number of comorbidities reported. Complete models are reported in Supplementary Tables S2 , S3 , Table and S4 .

*P < 0.05; **P < 0.01; ***P < 0.001.

POEM, Patient-oriented Eczema Measure; VOLP, value of lost productivity; WPAI, work productivity and impairment.

In the multivariable models, compared to those with mild AD, AD severity was associated with overall work impairment measured by the WPAI (adjusted difference 13.6% [95% CI: 3.0, 24.1] for moderately severe AD and adjusted difference 20.5% [95% CI: 8,3, 32.7] for severe to very severe AD) (Table 3 and Supplementary Table S3). AD severity was also associated with activity impairment as measured by the WPAI (adjusted difference 12.2% [95% CI: 3.0, 21.5] for moderately severe AD and adjusted difference 19.2% [95% CI: 8.3, 30.0] for severe to very severe AD).

Our multivariable model revealed a negative association between AD severity and HRQOL. Compared to those with mild AD, participants with moderately severe AD had lower health utility (adjusted difference −0.08 [95% CI: −0.16, −0.01]), as did participants with severe to very severe AD (adjusted difference −0.17 [95% CI: −0.26, −0.08] (Table 3 and Supplementary Table S4).

DISCUSSION

In this cross-sectional study involving participants from across Canada, we compared productivity loss and HRQOL between individuals with different levels of AD severity. When total, paid, and unpaid productivity losses were measured in hours using the VOLP questionnaire, participants who reported moderate to very severe symptoms of AD had, on average, greater productivity losses. However, we did not identify a statistically significant relationship between AD severity and productivity loss after adjusting for relevant covariates. When productivity losses were quantified as percent overall work impairment and percent activity impairment using the WPAI questionnaire, strong positive associations were identified between AD severity and percent impairment, and these associations remained significant after adjustment. HRQOL was assessed by calculating health utilities from responses to the VR-12 questionnaire, and in the adjusted model, AD severity was associated with lower health HRQOL.

Our findings regarding the association between AD severity and WPAI productivity loss extend results from other studies. For example, a large study involving US and European patients observed that greater AD severity, measured by the Patient-Oriented Scoring Atopic Dermatitis (PO-SCORAD) questionnaire, was associated with greater work and activity impairment measured by WPAI.¹⁵ Similarly, a US study identified that AD patients with inadequate disease control reported greater work and activity impairment measured by WPAI.⁴¹

Our observation that AD severity is associated with worse HRQOL corroborates prior research. Studies using the Dermatology Life Quality Index as a measure of HRQOL identified that individuals with greater AD severity had lower HRQOL.^1,8,10,13 Similar findings were observed when the EQ-5D-5L was used to capture health utilities.¹⁰ Our study expands upon this work by measuring health utilities using the VR-12. A recent study in BC concluded that the VR-12 might be a more comprehensive measure of health utility than the EQ-5D with respect to mental health symptoms.²³ To our knowledge, our study is the first to assess HRQOL among people with AD using the VR-12 and the first to estimate health utilities among people with AD in Canada.

The results of this study underscore the societal value of developing effective AD treatments and improving access to currently available treatments. For example, data from our study suggests that a treatment that reduces AD severity from severe or very severe (POEM score 17–28) to mildly severe (POEM score 0–7) could result in an adjusted 20.5% reduction in work impairment and an adjusted 19.2% reduction in activity impairment. From an HRQOL perspective, our data suggest that this degree of improvement in AD severity could result in an adjusted health utility improvement of 0.17.

Our study has several limitations.^25,26 First, because this was a cross-sectional study, we could not confirm causal relationships between the severity of AD and the outcomes measured. Second, the study sample may not represent all employed Canadians with AD, as participants were recruited through online convenience sampling. Third, while we observed trends in the expected direction across all outcomes, the study likely lacked sufficient statistical power to detect statistically significant differences between groups when productivity loss was measured using the VOLP questionnaire. Fourth, the VOLP and WPAI assessed productivity loss related to general health, rather than isolating loss specifically attributable to AD. Fifth, AD diagnosis was based solely on self-reported data rather than medical records, which could have led to the inclusion of participants without a confirmed diagnosis. Similarly, we relied exclusively on self-reports for comorbidity data.

There are several notable strengths of our study.^25,26 We collected data in both English and French from diverse regions across Canada, including participants representing a range of socioeconomic backgrounds and occupational settings. Additionally, we adopted a patient-centered approach by involving patient partners throughout the research process. This collaboration helped ensure that our methods and findings reflected the priorities and values of individuals living with atopic dermatitis (AD) and other chronic conditions. A key strength of the study was the careful selection of validated patient-reported outcome measures. We assessed disease severity using the POEM questionnaire as opposed to the PO-SCORAD, which has been used in prior similar studies.^8,15,41 A recent study comparing multiple methods of measuring AD severity revealed that the POEM may have stronger measurement properties than PO-SCORAD.⁴² We used two different questionnaires to measure productivity loss. To our knowledge, this is the first study to collect data using VOLP in AD, and the data collected using WPAI will allow for comparisons with other AD studies that used this measure.^14,15,17,18 Previous studies have found that the presenteeism hour loss estimated using the WPAI was much higher than the hour loss estimated using the presenteeism measurement method of the VOLP.^33,43 This might partially explain the different findings for the VOLP and WPAI productivity loss outcomes.

CONCLUSION

In conclusion, greater severity of AD was associated with greater work and activity impairment among employed adults and worse HRQOL. These findings demonstrate the economic impact of AD and highlight the potential societal value of effective interventions.

Footnotes

SUPPLEMENTARY MATERIAL

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