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Quebec Health-Related Quality-of-Life Population Norms Using the EQ-5D-5L: Decomposition by Sociodemographic Data and Health Problems

Open ArchivePublished:October 03, 2019DOI:https://doi.org/10.1016/j.jval.2019.08.008

      Abstract

      Objectives

      Population norms for the EQ-5D-5L were published in Canada but only for Alberta province. The purpose of this study was to derive Quebec population norms from the EQ-5D-5L.

      Methods

      The data came from a larger study conducted between September 2016 and March 2018 using elicitation techniques for a quality-adjusted life-year project. The online survey was distributed randomly in the province of Quebec. To best describe the entire population, data were stratified by various sociodemographic characteristics such as age, gender, urban and rural populations, whether disadvantaged or not, immigrant or nonimmigrant, and health problems.

      Results

      A total of 2704 (53.8%) respondents completed the EQ-5D-5L. Mean (95% confidence interval) and median (interquartile range) utility scores were 0.824 (0.818-0.829) and 0.867 (0.802-0.911), respectively. The EQ-VAS scores were estimated at 75.9 (75.2-76.6) and 80 (69-90). Subjects with lower scores were those who had a low or high body mass index; were smokers; were single, divorced, or widowed; had no children; were unemployed or sick; had lower education or lower annual income; and had a family or personal history of serious illness. Immigrants had higher scores. There was no difference in gender and urban or rural population. The score logically decreased with worsening health status, from a mean score of 0.896 (0.884-0.908) to 0.443 (0.384-0.501; P < .0001. Similar results were observed for subjects’ satisfaction with their health or life. Subjects with lower scores were less willing to take risks. Subjects who declared they were affected by health problems presented significant lower utility scores, ranging from 0.554 (nervous problem) to 0.750 (cancer), compared with those without health problems (0.871; confidence interval: 0.867-0.876).

      Conclusion

      This is the first study to present utility score norms for EQ-5D-5L for the Quebec population. These results will be useful for comparison with quality-adjusted life-year studies to better interpret their results. Moreover, utility norms were provided for 21 health problems, which was rarely done.

      Keywords

      Introduction

      For several years, economic studies have used cost-utility analysis with outcomes expressed as quality-adjusted life-year (QALY), which combines quantity of life with a measure of quality of life into a single score, namely, a utility score.
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      The Canadian guidelines for economic evaluation of health technologies encourages cost-utility analysis with outcomes expressed as QALY.
      Canadian Agency for Drugs and Technologies in Health
      Guidelines for the Economic Evaluation of Health Technologies: Canada.
      In addition, they encourage researchers to use estimates reflective of the general Canadian population.
      Canadian Agency for Drugs and Technologies in Health
      Guidelines for the Economic Evaluation of Health Technologies: Canada.
      Utility score norms estimated for a population may serve as a reference group, especially for studies that do not have a control group and want to estimate the effect of their intervention.
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      Using the Internet to collect EQ-5D norm scores: a valid alternative?.
      These data can also be used to document the burden of disease experienced by these individuals, particularly in comparison with other population groups and the general population, to help establish priority strategies in the provision of care for the population.
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      Sf-6d population norms.
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      Finally, the population norms can be used to better interpret the results obtained with studies using QALY by putting them into perspective.
      • Hopman W.M.
      • Towheed T.
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      • et al.
      Canadian normative data for the SF-36 health survey. Canadian Multicentre Osteoporosis Study Research Group.
      • Hawthorne G.
      • Osborne R.
      Population norms and meaningful differences for the Assessment of Quality of Life (AQoL) measure.
      Indeed, according to Hopman et al,
      • Hopman W.M.
      • Towheed T.
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      • et al.
      Canadian normative data for the SF-36 health survey. Canadian Multicentre Osteoporosis Study Research Group.
      population norms are the key to determining whether a group or individual scores above or below the average for their country, age, or gender.
      The EQ-5D is a preference-based measure widely used in cost-utility analysis.
      • Xie F.
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      • Gaebel K.
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      A time trade-off-derived value set of the EQ-5D-5L for Canada.
      • Ferreira L.N.
      • Ferreira P.L.
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      • Oppe M.
      EQ-5D Portuguese population norms.
      The original version, the EQ-5D-3L, comprised 5 dimensions with 3 levels each. A new version, the EQ-5D-5L, was recently developed, keeping the original 5 dimensions but expanding the response options from 3 to 5 levels to reflect no, slight, moderate, severe, and unable/extreme problems.
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      Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L).
      This allowed obtaining a wider range of health state possibilities. Population norms for the EQ-5D-5L were published in Canada but only for Alberta province. Otherwise, value sets for the EQ-5D instrument were published in Canada, a first for the short version EQ-5D-3L
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      Canadian valuation of EQ-5D health states: preliminary value set and considerations for future valuation studies.
      and a second for the long version EQ-5D-5L.
      • Xie F.
      • Pullenayegum E.
      • Gaebel K.
      • et al.
      A time trade-off-derived value set of the EQ-5D-5L for Canada.
      Nevertheless, no population norms were derived from these studies, and for the EQ-5D-5L, the authors indicated that the sample used cannot be considered as representative for the province of Quebec. Considering other health-related quality-of-life (HRQoL) measures, Canadian normative data were established for the SF-36 health survey, including the Quebec province.
      • Hopman W.M.
      • Towheed T.
      • Anastassiades T.
      • et al.
      Canadian normative data for the SF-36 health survey. Canadian Multicentre Osteoporosis Study Research Group.
      Specifically for preference-based measures, Guertin et al
      • Guertin J.R.
      • Feeny D.
      • Tarride J.-E.
      Age- and sex-specific Canadian utility norms, based on the 2013–2014 Canadian Community Health Survey.
      recently provided utility score norms for several age, gender, and jurisdiction strata in Canada, using the Health Utilities Index Mark 3.
      Quebec’s population is different from other Canadian provinces. Indeed, Quebec is the only Canadian province that has a predominantly French-speaking population, and health indicators are different between provinces.
      • Health
      Provincial and territorial ranking. How Canada performs.
      It is therefore important to have reference values for Quebec and not only for Canada for studies in this province.
      The purpose of this study was to derive Quebec population norms for the EQ-5D-5L. The specific objective was to describe the entire population, stratified for various sociodemographic characteristics of individuals, particularly for age, gender, urban and rural populations, whether disadvantaged or not, immigrant or nonimmigrant, and health problems.

      Methods

      Data

      The data come from a larger study conducted between September 2016 and March 2018 using elicitation techniques for a QALY project. Specifically, the aim of this larger study was to compare different elicitation methods for QALY (i.e., standard gamble versus discrete choice experiment). The company Research Now SSI (Survey Sampling International) distributed the online survey randomly among its members in the province of Quebec. Members decided whether they were interested in participating by clicking within a list of surveys provided by Research Now SSI. The first page of the survey presented the survey content, usefulness of this study, advantages and disadvantages for the participant, and a contact person for questions or complaints. The company made sure there could not be multiple completions by using a unique ID by respondent. As the EQ-5D-5L was the last issue of the survey, only those who completed it entirely were selected for analysis. Respondents did not receive an amount directly for completing the survey. The survey company gave them an amount depending on the number of questionnaires answered.

      Variables

      The population HRQoL was measured with the EQ-5D-5L questionnaire, which included 5 dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) with 5 levels each, ranging from no problem to extreme problem. The EQ-5D-5L questionnaire also included a vertical visual analog scale (VAS), with 100 on the top representing the “best imaginable health state” and 0 at the bottom representing the “worst imaginable health state.” Health utility scores were calculated with the value set developed by Xie et al
      • Xie F.
      • Pullenayegum E.
      • Gaebel K.
      • et al.
      A time trade-off-derived value set of the EQ-5D-5L for Canada.
      and using their recommended model. They used a composite time trade-off composed of a traditional and a lead time trade-off. Their sampling was from the general population of 4 cities across Canada, including Montreal, a city in the Quebec province. The health utilities elicited ranged from –0.148 for the worst (55555) to 0.949 for the best (11111) EQ-5D-5L health states. Because health utility scores were calculated with a linear model, worst and best states were different from 0 and 1. The ceiling effect was the proportion of respondents reporting “no problems” for all dimensions.
      The questionnaire included a large number of covariates to describe the sample, including sociodemographic variables (age, gender, occupation, education, marital status, annual income, smoking), if the respondent lives with another adult, is responsible for children younger than 18 years, lives in a rural or urban area, has home ownership (yes/no), has residency status in Canada, has a personal or family history of health problem, has a self-reported health problem affecting quality of life, and their general health status and satisfaction with general health. Health status was measured with a 5-point Likert scale ranging from excellent to poor. Health and life satisfaction scores were measured with a Likert scale ranging from 0 to 10, from not at all satisfied to fully satisfied. Willingness to take risks was measured using a VAS, where 0 represented hate taking risks and 10 represented love taking risks.

      Statistical Analysis

      The health utility score was estimated with the mean (95% confidence interval [CI]) and median (interquartile range [IQR]). To evaluate whether the sample was representative of the general population, descriptive statistics of the Quebec population were added when available by Statistique Canada or the Institut de la Statistique du Québec. To describe utility scores among subpopulations, EQ-5D-5L scores were compared with covariables using Kruskal-Wallis and Wilcoxon tests. A multivariate ordinary least squares regression model was computed on inverse logarithm utility score transformation to determine which demographic characteristics were important indicators. Inverse logarithm transformation was used to obtain residuals normally distributed. Only demographic variables with P < .05 were included in the multivariate model (ie, age, gender, body mass index [BMI], smoking, married/living with a partner, employed, education in years, annual income, living with an adult, have a child, history of serious illness, family history of serious illness, home ownership, Canada as country of origin, health status, health satisfaction, life satisfaction, willingness to take risks). The White correction was used to control heteroscedasticity. As the EQ-5D-5L was requested at the end of the questionnaire, there were no missing data for the variables included in the model, so no imputation was needed. The ceiling effect was calculated for each subpopulation. The health utility score was described for age categories, BMI, and health status for men and women separately. The health utility score was calculated for each HRQoL. Finally, the percentage of patients for each level of each dimension was presented and compared by gender and age. All analyses were also computed for EQ-VAS and presented in a supplementary analysis. Analyses were computed with SAS software (version 9.4; SAS Institute Inc, Cary, NC) and graphed with GraphPad Prism version 7.00 for Windows. A P value less than .05 was considered significant.

      Ethical Approval

      This project was approved by the institutional ethics committee (Comité d’éthique de la recherche of the CIUSSS de l'Estrie–CHUS #2016-1350). The subject’s consent was obtained by clicking on the start button at the end of the explanatory letter. All questionnaires were anonymous, and the data were stored on a protected network at our institution to ensure confidentiality and protection of the respondents.

      Results

      Sample Characteristics

      Of the 5028 subjects who were directed to the explanatory letter, 366 (7.3%) did not go further; 1958 (38.9%) started it, but did not complete until the end; and 2704 (53.8%) completed the EQ-5D-5L, but 9 did not complete the EQ-VAS. The 2324 subjects who did not complete the questionnaire were mostly older, were alone, had no children, were retired, were less educated, had lower income, and had more health problems (Supplementary Table 1 found at https://doi.org/10.1016/j.jval.2019.08.008). The 2704 completers were globally representative of the general population but had a little more education, were less urban, and fewer were immigrants (Table 1). People older than 75 years were less well represented.
      Table 1Study sample characteristics: comparison with Quebec general population aged 18 years or older and EQ-5D-5L index.
      SampleGeneral population aged 18 y or older
      General population for education was 25 to 64 years. For history of serious illness, Canadian citizenship, Canada as origins country, and health status, the population was 15 years and older.
      EQ-5D-5L index% Ceiling effect
      Mean (95% CI)Median (IQR)P value
      OverallN = 27046 842 2280.824 (0.818-0.829)0.867 (0.802-0.911)20.8%
      Age, y
       18-247.1%10.2%0.843 (0.824-0.863)0.874 (0.829-0.949)<.000125.5%
       25-297.1%8.2%0.865 (0.849-0.881)0.905 (0.829-0.949)36.8%
       30-349.4%8.0%0.837 (0.820-0.854)0.867 (0.808-0.949)25.3%
       35-398.9%8.7%0.837 (0.818-0.855)0.870 (0.823-0.949)25.8%
       40-448.1%8.0%0.824 (0.802-0.845)0.867 (0.808-0.911)19.1%
       45-498.7%7.7%0.804 (0.779-0.830)0.867 (0.788-0.911)20.8%
       50-5413.1%8.9%0.798 (0.779-0.816)0.866 (0.763-0.905)15.6%
       55-5912.2%9.3%0.805 (0.787-0.824)0.867 (0.784-0.905)15.2%
       60-6411.5%8.4%0.822 (0.805-0.839)0.867 (0.802-0.905)17.7%
       65-698.6%7.2%0.832 (0.814-0.850)0.867 (0.802-0.905)18.0%
       70-744.3%5.8%0.827 (0.799-0.854)0.866 (0.802-0.905)16.5%
       ≥ 751.1%9.7%0.803 (0.736-0.870)0.867 (0.782-0.905)13.8%
      Gender
       Women55.8 %50.6%0.819 (0.811-0.827)0.867 (0.790-0.910).000417.8%
       Men44.2 %49.4%0.829 (0.820-0.838)0.872 (0.807-0.911)24.6%
      Body mass index, kg/m2
       <18.53.1%2.4%0.795 (0.754-0.835)0.867 (0.708-0.949)<.000125.3%
       18.5-24.934.5%43.9%0.848 (0.839-0.856)0.874 (0.829-0.920)24.9%
       25-29.933.2%34.9%0.841 (0.832-0.850)0.874 (0.810-0.911)22.8%
       30-34.916.6%18.8%
      Last categories for body mass index (BMI) included BMI ≥30.
      0.798 (0.781-0.815)0.866 (0.782-0.905)16.5%
       35-39.97.5%0.760 (0.733-0.787)0.828 (0.706-0.905)9.4%
       ≥405.2%0.737 (0.702-0.773)0.808 (0.680-0.883)7.9%
      Smoking
       No76.7%81.4%0.834 (0.827-0.840)0.867 (0.810-0.911)<.000121.7%
       Yes23.3%18.6%0.791 (0.777-0.805)0.847 (0.745-0.905)17.7%
      Marital status
       Married/living with a partner55.9%56.3%0.838 (0.830-0.845)0.867 (0.810-0.911)<.000122.0%
       Single29.5%29.4%0.806 (0.793-0.818)0.867 (0.764-0.911)20.7%
       Divorced/separated11.7%8.6%0.808 (0.789-0.826)0.867 (0.788-0.905)16.7%
       Widowed2.8%5.7%0.795 (0.760-0.830)0.863 (0.741-0.905)14.5%
      Occupational status
       Employed52.9%59.5%0.851 (0.844-0.857)0.874 (0.829-0.949)<.000125.9%
       Student6.3%3.3%0.854 (0.837-0.871)0.874 (0.829-0.911)23.4%
       Retired24.4%27.4%
      For occupational status, 27.4% were “other” (probably included retired and at home).
      0.814 (0.802-0.827)0.867 (0.785-0.905)16.8%
       At home7.0%0.780 (0.754-0.806)0.829 (0.726-0.905)9.0%
       Unemployed6.1%7.2%0.767 (0.739-0.794)0.829 (0.679-0.905)12.7%
       Sick and parental leave3.3%2.5%0.596 (0.542-0.650)0.660 (0.423-0.807)3.4%
      Education
       Secondary or less26.9%31.8%0.782 (0.768-0.796)0.847 (0.726-0.905)<.000115.5%
       Diploma of professional studies14.3%19.8%0.821 (0.806-0.836)0.867 (0.796-0.911)18.8%
       CEGEP28.3%19.0%0.835 (0.824-0.845)0.874 (0.809-0.911)22.5%
       Baccalaureate23.3%25.5%
      For education, 25.5% included baccalaureate, masters, and PhD degrees.
      0.849 (0.839-0.858)0.872 (0.828-0.911)23.0%
       Master6.1%0.865 (0.849-0.880)0.905 (0.840-0.949)29.9%
       PhD1.1%0.825 (0.756-0.894)0.867 (0.763-0.949)33.3%
      Annual household income, $CAN
       <50001.9%0.770 (0.713-0.826)0.829 (0.707-0.905)<.000115.7%
       5000-99992.2%0.737 (0.686-0.789)0.808 (0.622-0.874)5.3%
       10 000-14 9994.9%0.670 (0.629-0.710)0.726 (0.542-0.847)16.9%
       15 000-19 9994.4%0.809 (0.781-0.837)0.863 (0.785-0.905)21.7%
       20 000-24 9996.7%0.810 (0.784-0.835)0.867 (0.784-0.911)15.0%
       25 000-34 99911.6%0.802 (0.783-0.821)0.866 (0.770-0.905)23.1%
       35 000-44 99911.7%0.817 (0.798-0.837)0.867 (0.805-0.911)21.3%
       45 000-54 99911.8%0.840 (0.826-0.854)0.867 (0.795-0.911)6.8%
       55 000-64 9998.9%0.849 (0.834-0.864)0.867 (0.825-0.911)20.0%
       65 000-74 9998.5%0.844 (0.827-0.861)0.874 (0.823-0.911)23.0%
       75 000-84 9995.9%0.854 (0.837-0.871)0.885 (0.825-0.911)23.1%
       85 000-99 9998.2%0.855 (0.837-0.872)0.905 (0.835-0.949)27.1%
       100 000-119 9996.1%0.844 (0.821-0.868)0.905 (0.828-0.949)25.3%
       120 000-149 9994.1%0.866 (0.851-0.882)0.905 (0.829-0.911)22.5%
       ≥150 0003.2%0.882 (0.863-0.902)0.905 (0.867-0.949)36.0%
       Mean ($CAN)$58 592$61 061
      Living with an adult
       No29.4%0.793 (0.780-0.806)0.867 (0.745-0.907)<.000118.5%
       Yes70.6%0.836 (0.830-0.843)0.867 (0.810-0.911)21.8%
      Have a child
       No77.0%0.818 (0.811-0.825)0.867 (0.790-0.911).000620.0%
       Yes23.0%0.843 (0.832-0.853)0.867 (0.823-0.911)23.3%
      History of serious illness
       No77.6%0.848 (0.843-0.854)0.874 (0.829-0.911)<.000123.9%
       Yes22.4%0.737 (0.721-0.754)0.808 (0.669-0.872)9.9%
      Family history of serious illness
       No42.1%0.841 (0.832-0.849)0.905 (0.823-0.949)<.000126.8%
       Yes57.9%0.811 (0.803-0.819)0.867 (0.784-0.905)16.4%
      Urban area
       No31.3%19.4%0.825 (0.815-0.835)0.867 (0.790-0.911).466120.0%
       Yes68.7%80.6%0.823 (0.816-0.830)0.867 (0.803-0.911)21.2%
      Owning a home
       No41.6%46.2%0.799 (0.788-0.809)0.866 (0.763-0.905)<.000118.4%
       Yes58.4%53.8%0.841 (0.834-0.848)0.874 (0.821-0.911)22.5%
      Canadian citizenship
       Canadian citizen96.7%95.0%0.822 (0.816-0.828)0.867 (0.802-0.911).072020.6%
       Permanent residence2.8%0.858 (0.828-0.887)0.905 (0.847-0.929)35.7%
       Temporary residence permit0.5%5.0%0.878 (0.838-0.918)0.870 (0.829-0.949)24.0%
      Canada as parents’ origins country
       No11.0%0.846 (0.830-0.863)0.874 (0.829-0.911).000724.9%
       Yes89.0%0.821 (0.814-0.827)0.867 (0.790-0.911)20.3%
      Canada as origins country
       No8.2%16.8%0.863 (0.847-0.878)0.905 (0.847-0.949).000126.7%
       Yes91.8%83.2%0.820 (0.814-0.826)0.867 (0.790-0.911)20.3%
      Health status
       Excellent12.5%89.7%
      For health status, 89.7% considered themselves to be in good health (excellent to good).
      0.896 (0.884-0.908)0.949 (0.905-0.949)<.000150.3%
       Very good37.1%0.879 (0.873-0.884)0.905 (0.867-0.949)27.7%
       Good37.9%0.815 (0.807-0.823)0.854 (0.785-0.905)10.4%
       Fair9.7%10.3%0.664 (0.640-0.687)0.724 (0.558-0.808)2.3%
       Poor2.8%0.443 (0.384-0.501)0.423 (0.227-0.660)1.3%
      Satisfaction with health
       0-38.5%0.582 (0.551-0.613)0.645 (0.404-0.771)<.00011.7%
       4-626.3%0.777 (0.765-0.789)0.828 (0.726-0.867)8.4%
       7-1065.1%0.874 (0.870-0.879)0.905 (0.860-0.949)28.3%
      Satisfaction with life
       0-35.7%0.608 (0.568-0.647)0.645 (0.447-0.810)<.00013.9%
       4-624.6%0.775 (0.763-0.788)0.829 (0.725-0.874)7.8%
       7-1069.7%0.858 (0.853-0.864)0.905 (0.829-0.949)26.7%
      Willingness to take risks
       0-329.5%0.786 (0.772-0.799)0.866 (0.742-0.905)<.000115.0%
       4-641.4%0.836 (0.828-0.845)0.867 (0.808-0.911)22.0%
       7-1029.0%0.843 (0.834-0.853)0.867 (0.810-0.911)25.0%
      CI indicates confidence interval; IQR, interquartile range (25th–75th percentiles).
      General population for education was 25 to 64 years. For history of serious illness, Canadian citizenship, Canada as origins country, and health status, the population was 15 years and older.
      Last categories for body mass index (BMI) included BMI ≥30.
      For occupational status, 27.4% were “other” (probably included retired and at home).
      § For education, 25.5% included baccalaureate, masters, and PhD degrees.
      For health status, 89.7% considered themselves to be in good health (excellent to good).

      EQ-5D-5L Utility Scores and EQ-VAS

      A histogram of the utility score distribution and EQ-VAS is presented in Figure 1. As expected, the distribution was not normal. The upper bound for utility scores was 0.949, and the lower bound was –0.148. Only 6 subjects had negative utility scores. Of the subjects, 20.8% had the highest EQ-5D-5L utility score (EQ-5D-5L utility score = 0.949, 11111 health state) and only 4.3% for the EQ-VAS (VAS = 100). The other most common health states were 11121, 11122, 11112, and 11123 in 14.5%, 11.4%, 6.7%, and 3.5% subjects, respectively. The mean (95% CI) and median (IQR) utility scores were estimated at 0.824 (0.818-0.829) and 0.867 (0.802-0.911), respectively (Table 1).
      Figure thumbnail gr1
      Figure 1Distribution of utility score and VAS for EQ-5D-5L. The values on the x-axis correspond to the central value with an interval of 0.05 for EQ-5D-5L score and 5 points for EQ-VAS. The first band/value corresponds to –0.148 to –0.10 for EQ-5D-5L score and 0 to 2.5 for EQ-VAS. The last band/value corresponds to the ceiling effect, 0.949 for utility score (n = 562, 20.8%) and 100% for VAS (n = 116, 4.3%). VAS indicates visual analogue scale.

      EQ-5D-5L Utility Scores and EQ-VAS According to Sample Characteristics

      Subjects with lower scores were those who had low or high BMI; were smokers; were single, divorced, or widowed; had no children; were unemployed or sick; had lower education or lower annual income; and had a family or personal history of serious illness (Table 1). Immigrants had higher scores. There was no difference in gender and urban or rural population. Logically, the score decreased with worsening health status, with a mean score of 0.896 (0.884-0.908) to 0.443 (0.384-0.501; P < .0001). Similar results were observed for subjects’ satisfaction with their health or life. Subjects with lower scores were less willing to take risks. The mean (95% CI) and median (IQR) EQ-VAS were estimated at 75.9 (75.2-76.6) and 80 (69-90), respectively (Supplementary Table 1). Similar results were observed for the EQ-VAS and are presented in a supplementary file. In the multivariate regression model, because EQ-5D-5L values were transformed with an inverse logarithm to obtain a normal distribution of residues, the estimates must be interpreted in the opposite sense. Women of older age with higher BMI, history of serious illness, and family history of serious illness independently and significantly reduced the health utility score. On the contrary, employment, higher education, living with an adult, higher health status, higher health, and life satisfaction independently and significantly increased the health utility score (Supplementary Table 5).

      Norm Scores for Age, BMI, Health Status, and Comorbidity According to Gender

      The EQ-5D-5L utility score was presented by age, BMI, and health status categories and divided by gender (Table 2). Results were almost similar for men and women. The distribution was different for age between genders. For men, the utility score decreased with age, and the lowest score was for those 75 years and older. For women, the lowest mean score was between 45 and 59 years, and the lowest median score was for those between 50 and 54 years. A description of the EQ-5D-5L utility score according to problems affecting quality of life is presented in Table 3. For men, problems that affected them the most were the nervous system, injury, and musculoskeletal problems other than osteoarthritis or arthritis. For women, it was principally genitourinary problems, but these were represented in only 13 subjects. In addition to genitourinary issues, nervous system and musculoskeletal problems other than osteoarthritis or arthritis were most common, as in the men.
      Table 2EQ-5D-5L index score according to gender.
      MenWomen
      nMean (95% CI)Median (IQR)nMean (95% CI)Median (IQR)
      Age, y
       18-24620.835 (0.797-0.873)0.905 (0.828-0.949)1300.847 (0.824-0.869)0.874 (0.829-0.911)
       25-29680.861 (0.826-0.896)0.911 (0.829-0.949)1250.867 (0.850-0.884)0.874 (0.829-0.949)
       30-341010.827 (0.795-0.858)0.905 (0.785-0.949)1520.844 (0.824-0.864)0.867 (0.829-0.911)
       35-39930.864 (0.839-0.890)0.905 (0.847-0.949)1470.819 (0.794-0.844)0.867 (0.771-0.911)
       40-44870.848 (0.814-0.881)0.905 (0.829-0.949)1330.808 (0.781-0.835)0.867 (0.784-0.905)
       45-491120.822 (0.788-0.855)0.879 (0.806-0.920)1240.789 (0.752-0.826)0.867 (0.765-0.905)
       50-541530.803 (0.773-0.833)0.867 (0.784-0.905)2000.793 (0.770-0.816)0.847 (0.751-0.905)
       55-591600.812 (0.785-0.840)0.867 (0.784-0.908)1690.799 (0.773-0.825)0.866 (0.784-0.905)
       60-641570.822 (0.798-0.845)0.867 (0.790-0.905)1540.822 (0.796-0.847)0.867 (0.807-0.905)
       65-691260.842 (0.819-0.866)0.867 (0.810-0.905)1070.820 (0.792-0.848)0.867 (0.771-0.905)
       70-74580.836 (0.795-0.876)0.872 (0.803-0.911)570.818 (0.780-0.855)0.866 (0.802-0.905)
       ≥75180.779 (0.680-0.877)0.856 (0.743-0.905)110.842 (0.756-0.929)0.867 (0.828-0.949)
      Body mass index, kg/m2
       <18.5260.755 (0.672-0.837)0.820 (0.704-0.911)570.813 (0.767-0.860)0.867 (0.725-0.949)
       18.5-24.93600.847 (0.831-0.862)0.905 (0.829-0.949)5720.848 (0.839-0.858)0.867 (0.829-0.911)
       25-29.94830.849 (0.838-0.861)0.905 (0.828-0.911)4150.832 (0.818-0.846)0.867 (0.803-0.911)
       30-34.92000.812 (0.786-0.838)0.867 (0.795-0.911)2490.787 (0.765-0.810)0.854 (0.764-0.905)
       35-39.9770.740 (0.693-0.787)0.821 (0.679-0.885)1250.773 (0.740-0.806)0.828 (0.725-0.905)
       ≥40490.744 (0.687-0.801)0.800 (0.708-0.905)910.734 (0.688-0.780)0.829 (0.673-0.867)
      Self-reported health status
       Excellent1640.894 (0.875-0.914)0.949 (0.905-0.949)1740.897 (0.882-0.912)0.911 (0.867-0.949)
       Very good4560.885 (0.877-0.893)0.905 (0.867-0.949)5470.873 (0.866-0.880)0.905 (0.866-0.911)
       Good4300.818 (0.805-0.830)0.859 (0.795-0.905)5950.813 (0.803-0.824)0.847 (0.784-0.905)
       Fair1070.669 (0.632-0.705)0.726 (0.560-0.802)1540.660 (0.630-0.691)0.717 (0.558-0.810)
       Poor380.447 (0.360-0.533)0.442 (0.255-0.660)390.439 (0.357-0.521)0.411 (0.224-0.616)
      CI indicates confidence interval; IQR, interquartile range (25th-75th percentiles).
      Table 3EQ-5D-5L index score according to problems affecting HRQoL.
      TotalMenWomenP value
      nMean (95% CI)Median (IQR)nMean (95% CI)Median (IQR)nMean (95% CI)Median (IQR)
      No problem18410.871 (0.867-0.876)0.905 (0.847-0.949)8030.877 (0.870-0.884)0.905 (0.866-0.949)10380.867 (0.861-0.873)0.885 (0.846-0.911)<.0001
      Self-reported problems affecting HRQoL
      Problems affecting HRQoL included all problems listed below. Subject may have more than 1 problem.
      8630.722 (0.708-0.735)0.802 (0.645-0.867)3920.731 (0.710-0.752)0.807 (0.666-0.867)4710.714 (0.696-0.732)0.782 (0.625-0.866).0613
       Anxiety/stress3320.653 (0.629-0.677)0.726 (0.546-0.810)1310.645 (0.603-0.686)0.738 (0.542-0.823)2010.658 (0.628-0.688)0.726 (0.552-0.810).9231
       Arthritis1080.642 (0.596-0.688)0.726 (0.522-0.831)540.649 (0.580-0.718)0.753 (0.503-0.828)540.635 (0.571-0.699)0.702 (0.524-0.841).5048
       Cancer580.750 (0.695-0.805)0.808 (0.713-0.867)300.761 (0.681-0.841)0.816 (0.785-0.892)280.738 (0.658-0.819)0.797 (0.693-0.867).3416
       Cardiac790.675 (0.622-0.727)0.771 (0.558-0.846)590.677 (0.613-0.741)0.782 (0.559-0.847)200.669 (0.573-0.764)0.755 (0.527-0.819).5166
       COPD520.679 (0.619-0.738)0.783 (0.508-0.819)290.677 (0.596-0.758)0.795 (0.496-0.810)230.680 (0.585-0.776)0.771 (0.520-0.841).7963
       Diabetes2800.740 (0.715-0.766)0.808 (0.679-0.905)1780.750 (0.719-0.781)0.810 (0.718-0.905)1020.723 (0.678-0.767)0.805 (0.645-0.905).3404
       Gastrointestinal1350.657 (0.619-0.695)0.726 (0.558-0.828)460.660 (0.592-0.727)0.732 (0.561-0.823)890.656 (0.608-0.703)0.726 (0.558-0.828).9076
       Genitourinary360.610 (0.517-0.703)0.745 (0.419-0.815)230.680 (0.579-0.781)0.764 (0.561-0.823)130.486 (0.301-0.672)0.611 (0.186-0.746).0463
       Hypertension2720.709 (0.682-0.736)0.802 (0.657-0.863)1220.696 (0.654-0.737)0.786 (0.617-0.846)1500.720 (0.684-0.755)0.805 (0.668-0.867).2772
       Injury540.589 (0.519-0.660)0.658 (0.401-0.784)270.553 (0.446-0.660)0.655 (0.353-0.764)270.626 (0.529-0.722)0.675 (0.447-0.808).2719
       Insomnia2630.652 (0.624-0.681)0.738 (0.538-0.828)1010.657 (0.609-0.704)0.745 (0.542-0.828)1620.650 (0.614-0.685)0.726 (0.522-0.829).6903
       Mental disorder1060.645 (0.600-0.689)0.712 (0.503-0.823)340.699 (0.626-0.771)0.785 (0.587-0.847)720.619 (0.563-0.676)0.664 (0.458-0.810).0867
       Nervous system610.554 (0.483-0.626)0.616 (0.310-0.770)250.517 (0.398-0.636)0.582 (0.219-0.763)360.580 (0.487-0.673)0.626 (0.371-0.803).3709
       Osteoarthritis3310.696 (0.674-0.718)0.764 (0.620-0.841)1240.684 (0.646-0.723)0.763 (0.577-0.828)2070.703 (0.675-0.730)0.765 (0.642-0.841).5103
       Other musculoskeletal1460.586 (0.546-0.627)0.660 (0.423-0.789)590.569 (0.501-0.637)0.660 (0.362-0.802)870.598 (0.548-0.648)0.668 (0.457-0.789).6798
       Other problem240.634 (0.558-0.710)0.648 (0.558-0.774)160.644 (0.550-0.739)0.639 (0.551-0.803)80.615 (0.451-0.779)0.662 (0.558-0.745).8065
      Other respiratory problem1050.672 (0.627-0.717)0.771 (0.544-0.829)370.702 (0.636-0.767)0.785 (0.544-0.829)680.655 (0.595-0.715)0.767 (0.534-0.838).4623
       Pain3670.631 (0.607-0.654)0.718 (0.505-0.803)1550.624 (0.586-0.661)0.725 (0.503-0.802)2120.636 (0.605-0.666)0.717 (0.520-0.803).7761
       Stroke210.684 (0.605-0.763)0.726 (0.616-0.808)130.664 (0.544-0.783)0.726 (0.616-0.800)80.717 (0.610-0.824)0.745 (0.629-0.825).6377
       Thyroid1260.702 (0.665-0.740)0.771 (0.600-0.853)350.644 (0.562-0.725)0.726 (0.503-0.828)910.725 (0.684-0.766)0.802 (0.655-0.866).0479
       Tired3260.633 (0.608-0.658)0.717 (0.520-0.808)1380.647 (0.608-0.687)0.735 (0.538-0.810)1880.623 (0.589-0.656)0.706 (0.499-0.803).2280
      CI indicates confidence interval; COPD, chronic obstructive pulmonary disease; HRQoL, health-related quality of life; IQR, interquartile range (25th-75th percentiles).
      Problems affecting HRQoL included all problems listed below. Subject may have more than 1 problem.
      When the 5 dimensions of the EQ-5D-5L were considered separately (Table 4), 27.1% considered having mobility problems, 8.4% self-care problems, 29.1% problems for usual activity, 67.9% pain or discomfort, and 53.3% anxiety or depression. Women had significantly fewer self-care problems (P = .03), more pain or discomfort (P = .01), and more anxiety or depression (P < .001). Distributions by age categories and gender are presented in Supplementary Table 6. The difference between genders was principally between 25 and 35 years for self-care problems, between 25 and 50 years for pain or discomfort, and between 35 and 39 years for anxiety or depression.
      Table 4Reported problems by 5 dimensions of the EQ-5D-5L (%).
      TotalMenWomenP value
      Mobility
       No problems72.972.273.4.9625
       Slight problems15.615.715.4
       Moderate problems8.18.57.9
       Severe problems2.82.92.7
       Incapacity0.70.70.7
      Self-care
       No problems91.690.092.8.0348
       Slight problems4.95.94.2
       Moderate problems2.62.72.5
       Severe problems0.71.10.3
       Incapacity0.30.30.3
      Usual activity
       No problems70.972.469.7.4580
       Slight problems18.116.619.4
       Moderate problems7.77.97.6
       Severe problems2.92.82.9
       Incapacity0.40.40.4
      Pain/discomfort
       No32.135.629.3.0140
       Slight45.243.346.7
       Moderate17.416.318.3
       Severe4.74.35.0
       Extreme0.70.60.8
      Anxiety/depression
       No46.852.142.5<.0001
       Slight32.429.434.7
       Moderate14.412.416.0
       Severe5.15.25.0
       Extreme1.41.01.7

      Discussion

      The objective was to establish population norms for Quebec, a province of Canada. To our knowledge, this is the first Quebec study to report EQ-5D-5L results for a randomly selected large sample. This will help better compare utility values in a different cultural setting and provide reference values for clinical studies conducted in Quebec.
      Some studies have established population standards for Canada, but some do not include Quebec,
      • Bansback N.
      • Tsuchiya A.
      • Brazier J.
      • Anis A.
      Canadian valuation of EQ-5D health states: preliminary value set and considerations for future valuation studies.
      • Health Quality Council of Alberta
      EQ-5D-5L Index Norms for Alberta Population.
      • Health Quality Council of Alberta
      2014 Alberta Population Norms for EQ-5D-5L.
      or they use utility scores other than the EQ-5D-5L,
      • Hopman W.M.
      • Towheed T.
      • Anastassiades T.
      • et al.
      Canadian normative data for the SF-36 health survey. Canadian Multicentre Osteoporosis Study Research Group.
      • Guertin J.R.
      • Feeny D.
      • Tarride J.-E.
      Age- and sex-specific Canadian utility norms, based on the 2013–2014 Canadian Community Health Survey.
      which is, however, the most widely used multiattribute utility instrument in the world.
      • Richardson J.
      • McKie J.
      • Bariola E.
      Multiattribute utility instruments and their use.
      Results for the EQ-5D-5L from Alberta province clearly showed a decrease in the age scores (0.88 to 0.82) with slightly higher values in men, but these were not significant. In our case, the EQ-5D-5L is lower in men 75 years and older, but this decrease is not as dramatic as for Alberta.
      • Health Quality Council of Alberta
      EQ-5D-5L Index Norms for Alberta Population.
      For women, it is rather the categories 45 to 59 years that are the worst, suggesting that older participants were in better health and possibly less representative of their cohort, unless this means the first years of retirement are a period during which people may benefit more from their life, thus experiencing a better HRQoL.
      • Midanik L.T.
      • Soghikian K.
      • Ransom L.J.
      • Tekawa I.S.
      The effect of retirement on mental health and health behaviors: the Kaiser Permanente Retirement Study.
      • Kim J.E.
      • Moen P.
      Retirement transitions, gender, and psychological well-being: a life-course, ecological model.
      In Alberta, the median (IQR) EQ-5D-5L index scores for men and women were 0.90 (0.83, 0.95) and 0.90 (0.82, 0.95), respectively, which was slightly higher than our results at 0.87 (0.81-0.91) and 0.87 (0.79-0.91), but their histogram distribution was similar to ours.
      • Health Quality Council of Alberta
      EQ-5D-5L Index Norms for Alberta Population.
      When comparing the percentage of patients who have problems (greater than level 1 in the EQ-5D-5L) for each item separately, patients in Alberta
      • Health Quality Council of Alberta
      2014 Alberta Population Norms for EQ-5D-5L.
      have fewer problems than our patients, but they were also younger and less representative of the general population.
      This study also confirmed some assumptions made in the literature regarding the association between sociodemographic variables and HRQoL. For example, we found lower utility scores for low and high BMI
      • Norman R.
      • Church J.
      • van den Berg B.
      • Goodall S.
      Australian health-related quality of life population norms derived from the SF-6D.
      • Wee H.-L.
      • Cheung Y.-B.
      • Loke W.-C.
      • et al.
      The association of body mass index with health-related quality of life: an exploratory study in a multiethnic Asian population.
      as well as for single/divorced/widowed respondents and those not living with another adult.
      • Steptoe A.
      • Shankar A.
      • Demakakos P.
      • Wardle J.
      Social isolation, loneliness, and all-cause mortality in older men and women.
      A number of people living alone may suffer from social isolation, and isolated people may experience financial stress, which could lower their well-being.
      • Wickrama K.A.S.
      • Lorenz F.O.
      • Conger R.D.
      • et al.
      Changes in family financial circumstances and the physical health of married and recently divorced mothers.
      • Turner H.A.
      Stress, social resources, and depression among never-married and divorced rural mothers.
      A strength of our study is that the sample size is considerable and generally representative of the population. Nevertheless, those aged 75 and older are not as well represented. This may be a limitation of an online sample because older people are generally less connected to the Internet.
      • Zickuhr K.
      • Madden M.
      Older Adults and Internet Use.
      Considering the aging population, it would have been interesting to have more subjects aged 75 and older. Another limitation was that respondents were more educated, and rural people slightly more represented. In addition, the utility score increased with education, as demonstrated in other studies.
      • Ferreira L.N.
      • Ferreira P.L.
      • Pereira L.N.
      • Rowen D.
      • Brazier J.E.
      Exploring the consistency of the SF-6D.
      This may limit the generalization of the results. As it was an online survey, it would have been difficult to change the response rates by categories, unlike a telephone study, as in Ferreira et al,
      • Ferreira L.N.
      • Ferreira P.L.
      • Pereira L.N.
      • Oppe M.
      EQ-5D Portuguese population norms.
      who contacted 6 times more subjects aged 70 years and older to have a better representation.
      Another limitation is that there is no statistical model for calculating EQ-5D-5L scores based on the preferences of the Quebec population (i.e., no value set), but at least the equation used
      • Xie F.
      • Pullenayegum E.
      • Gaebel K.
      • et al.
      A time trade-off-derived value set of the EQ-5D-5L for Canada.
      is a Canadian one and includes data from Quebec. Another strength of our study was that we presented health utility scores according to a wide range of variables, including but not limited to several age categories, BMI, and health status for men and women separately. This makes it easier for other studies to compare their data to our data. In addition, our study is one of the few to provide utility scores for various health problems. As in van den Berg,
      • van den Berg B.
      Sf-6d population norms.
      we found a high heterogeneity in the utility scores associated with specific health problems, which could be useful for healthcare decision makers in their priority exercises. On the other hand because numbers are quite small for some health problems, these results may not be fully representative of the population and should be used with caution.
      Finally, as compared with other studies describing population norms with the EQ-5D-5L, our study is the only one showing a ceiling effect as low as 20.8%, whereas it is generally greater than 40%.
      • Ferreira L.N.
      • Ferreira P.L.
      • Pereira L.N.
      • Oppe M.
      EQ-5D Portuguese population norms.
      • McCaffrey N.
      • Kaambwa B.
      • Currow D.C.
      • Ratcliffe J.
      Health-related quality of life measured using the EQ-5D–5L: South Australian population norms.
      • Golicki D.
      • Niewada M.
      EQ-5D-5L Polish population norms.
      This result is more in relation to studies using another multiattribute utility instrument, such as the Health Utilities Index Mark 3
      • Guertin J.R.
      • Feeny D.
      • Tarride J.-E.
      Age- and sex-specific Canadian utility norms, based on the 2013–2014 Canadian Community Health Survey.
      and the SF-6D
      • Shiroiwa T.
      • Fukuda T.
      • Ikeda S.
      • et al.
      Japanese population norms for preference-based measures: EQ-5D-3L, EQ-5D-5L, AND SF-6D.
      (ie, 19% and 4%, respectively), thus indicating that our study is probably more representative in terms of health problems affecting the HRQoL of the population. Also, the results in Figure 1 showed more linearity than in previous studies,
      • Ferreira L.N.
      • Ferreira P.L.
      • Pereira L.N.
      • Oppe M.
      EQ-5D Portuguese population norms.
      • Guertin J.R.
      • Feeny D.
      • Tarride J.-E.
      Age- and sex-specific Canadian utility norms, based on the 2013–2014 Canadian Community Health Survey.
      which is more in line with what is expected from a representative sample.

      Conclusion

      This study provides utility score norms for the EQ-5D-5L for the Quebec population, a French-speaking province of Canada. These results could be used for other studies that do not have a control group or to compare populations. In addition, these results will be useful for comparing with QALY studies to better interpret their results and assist researchers in interpreting their findings. Moreover, utility norms are provided for 21 health problems, which has rarely been done.

      Acknowledgments

      This work was funded through a research fund of the Social Sciences and Humanities Research Council of Canada, Knowledge Development Grants Program 2015-2017, file number 430-2015-00712.

      Supplemental Material

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