Quality of life of the Canadian population using the VR-12: population norms for health utility values, summary component scores and domain scores

Generic health-related quality of life instruments—measures of self-perceived health status designed to be applicable across diverse groups of respondents, regardless of disease or demographics—have a multitude of applications in research and clinical care. These include as indicators of disease burden and health outcome, as case-mix indicators for risk adjustment, and at the individual patient-level for informing care [1‐5]. There is no gold standard of measurement for health-related quality of life, whether generic or disease-specific. For this reason, it is important that instrument-specific resources exist to assist with the interpretation of data. An example of such a resource is the establishment of reference data for population norms, which summarize health outcomes in the general population and across demographic and clinical subgroups. The availability of population norms enables researchers to compare estimates from study samples with a population reference. Such data are useful in multiple contexts, including tracking changes in health outcomes over time [6‐9], comparing populations with different health conditions [10], comparing between countries [11, 12], and modelling comparison groups in the evaluation of health technologies in the absence of primary data [13].

The Veterans RAND 12-item Health Survey (VR-12) and associated measures are among the most widely used instruments for assessing respondents’ (patients and non-patients) perceptions of health domains relevant to their quality of life [5, 14]. The VR-12 was developed from the Veterans RAND 36-item Health Survey, which was developed and modified from the original RAND version of the 36-item Health Survey version 1.0 (also known as the MOS SF-36) [15, 16]. Responses to the VR-12 can be used to generate (i) health utility values, (ii) summary component scores for mental health and physical health, and (iii) scores for each of the instrument’s eight domains. (Further details about the VR-12 are provided in the Methods section.) Population norms for the VR-12 have been described using data from over 170,000 respondents to the Medicare Health Outcomes Survey in the United States (US) [16] and a sample of 500 Chinese adults in Hong Kong [17]. There are no Canadian population norms for the VR-12. Previous studies have published Canadian population norms for health utility scores generated using other instruments, including the Health Utilities Index Mark 3 (HUI3) [13], EQ-5D-3L (Alberta only) [18], EQ-5D-5L [19, 20], and, for Quebec only, the SF-6Dv2 (albeit with preference weights derived from a representative sample of the United Kingdom (UK) population) [21].

Health utility values are an important input in the economic evaluation of health technologies [13, 22, 23], where they can be used to estimate quality-adjusted life years (QALYs) [24, 25]. A health utility value (also known as a health state value or a preference weight) is an index score anchored on a 0–1 scale, where zero is interpreted as a state equivalent to dead and one is considered ‘full health’. The value provides a representation of a utility, reflecting the description of a health state provided by the respondent (e.g., an individual completing the VR-12) and the value of this health state based on the preferences of a representative sample of the general population [24, 26]. Negative health utility values are possible, reflecting health states worse than dead. In Canada, guidelines for the economic evaluation of health technologies state that health preferences should reflect the general Canadian population [27]. Researchers/analysts are also encouraged to examine potential sources of heterogeneity that may lead to using different parameter-input values (such as health utility values) across subgroups. The provision of norms that reflect societal preferences, by univariate (e.g., age or gender) and multivariate (e.g., age and gender) stratifications, can facilitate this type of analysis [13, 27].

The objective of this study was to estimate Canadian population norms (health utility values, summary component scores and domain scores) for the VR-12, including norms by univariate and multivariate stratifications.

The study was approved by the University of British Columbia Behavioural Research Ethics Board (study number H18-00969). The Checklist for Reporting Results of Internet E-Surveys (CHERRIES) was followed in the preparation of this manuscript [28].

Of 8110 individuals who clicked on the survey invitation link, 6761 (83.4%) completed the survey and 6741 (99.7% of the 6761) were included in the analysis (12 were excluded based on age and eight excluded because of missing VR-12 data). Sample characteristics for the sample (weighted and unweighted), and the 2021 Canadian census are presented in Table 1. Our sample was broadly representative of the Canadian population on most characteristics but was more highly educated and more likely to report a higher household income.

This is the first study to present population norms for the VR-12, derived from a representative sample of Canadians. These norms provide insights into the health of Canadians, including how older Canadians tend to report higher mental health scores and lower physical health scores compared with younger Canadians, and how women tend to report lower mental and physical health scores compared with men.

There are many instruments available to measure health-related quality of life, including the VR-12 and related instruments (VR-36, SF-12, SF-36), EQ-5D instruments (EQ-5D-3L and EQ-5D-5L), the Health Utilities Index (HUI), and the PROMIS Global-10. There are Canadian population norms for the HUI3 [13], EQ-5D-3L (Alberta only) [18], EQ-5D-5L [19, 20], SF-12 (Alberta only) [18], SF-6Dv2 (Quebec only, with UK-derived preference weights) [21], and the SF-36 [37]. The Canadian Institute for Health Information (CIHI) recommends that the availability of population norms be a central consideration when choosing between available measures [38]. In reviewing available measures of health-related quality of life regarding effectiveness, meaningfulness, appropriateness, and feasibility criteria, CIHI concluded that the VR/SF instruments scored highly on all criteria relative to other measures. The VR-12 also has a Canadian health utility value set [29]—facilitating the estimation of QALYs from VR-12 data—and, based on the results presented here, population norms.

The mean VR-12 health utility value for Canadians was estimated to be 0.698. There is a large literature on health utility values. However, it is challenging to compare across studies. Different instruments conceptualize health in different ways, which results in variation in the number of component domains and the relative balance between different aspects of health [39]. Different health utility values are to be expected and may reflect underlying preferences [40‐42]; however, the variation may also reflect subtle differences in the sociodemographic characteristics of the samples or the elicitation technique used [43‐48]. Our estimated mean health utility value for the VR-12 (0.698) is lower than estimates from other studies. For example, studies of the SF-6D from the UK, Australia, Hong Kong, and China, estimated mean values ranging from 0.766 to 0.872 [49‐53]. A Canadian study of the HUI estimated a mean health utility value of 0.863 [13], while Canadian, Chinese, and US studies of the EQ-5D-5L estimated mean values of 0.864, 0.946 and 0.851 (from the face-to-face sample), respectively [20, 52, 54]. Conversely, our estimates are similar to Australian mean age- and sex-adjusted utility norms for the Assessment of Quality of Life six-dimension (AQoL-6D) and eight-dimension (AQoL-8D) instruments, which were 0.737 and 0.680, respectively [22]. These findings might be explained by the respective components of the instruments, as the AQoL instruments and the VR-12 include a higher proportion of items related to psychosocial health when compared with variants of the SF-6D and EQ-5D instruments. For example, five of the eight dimensions of the AQoL-8D cover psychosocial health, corresponding to 25 of the 35 items [55]. Five of the eight VR-12 items used to calculate health utility values are related to mental health. A 2021 systematic review found that the SF-12, which is closely related to the VR-12, fully captured three of seven domains of mental health that were highly valued by people with mental health problems, and partially captured one additional domain [56]. By comparison, in the same study, the EQ-5D instruments fully captured one of the seven domains and partially captured two. The systematic review found that other generic (e.g., Quality of Life Index [57]) and condition-specific (e.g., Lancashire Quality of Life Profile [58]) instruments captured more of the domains of mental health that were highly valued by people with mental health problems. Neither of these instruments has a Canadian value set, which would enable their use in economic evaluation. The ability of the VR-12 to independently assess multiple mental health domains may be an advantage. Measures with fewer mental health domains may miss important aspects of mental health or conflate different domains by grouping them together. For example, the one mental health dimension included in the EQ-5D-5L measures two distinct aspects of mental health—anxiety and depression [59].

In our cross-sectional survey, we identified that people in older age groups provide VR-12 responses that correspond with higher mean health utility values. Previous studies have found different patterns with respect to age, including an age-related monotonic decline in health utility values for the SF-6D [50] and AQoL-4D [60] instruments, and a u-shaped utility curve for the AQoL-6D and AQoL-8D instruments [22]. The differences in these trajectories may reflect the items captured by each instrument. Evidence suggests that instruments with a higher proportion of items related to physical health tend to exhibit a monotonic decline, while those with a higher proportion of items related to mental health tend to exhibit a u-shaped curve given older age groups tend to report higher mental health scores [22, 37, 61]. In our study, higher scores in the mental health and social functioning domains in older Canadians seems to be driving the higher health utility scores in older ages. There was some evidence of lower physical health scores in older age groups for the bodily pain, physical functioning, and role physical domains, however these differences were modest in comparison with the age-related increase in scores on the mental health domains.

We observed that females reported lower scores than males. This finding was consistent across health utility values, summary component scores, and domain scores. A study of Medicare beneficiaries in the US that reported norms for the VR-12 also found that females reported lower mean PCS and MCS scores than males [16]. This general observation has been observed for other instruments [22, 23, 37]. It is possible men and women with the same health status may interpret and respond differently to the items (known as differential item functioning). However, a 2017 study of the VR-12, which included over 270,000 respondents, concluded there was no evidence of differential item functioning at the domain level across genders [62]. There were statistically significant differences for some items, although the magnitudes of these differences were considered negligible. This suggests that the observed gender differences may reflect differences in health status. A 2016 systematic review of self-reported health data from 59 countries found that women systematically reported lower health and functional status than males [63]. This effect was present across all age groups and in both low- and high-income countries. The authors suggested that both societal (e.g., gender inequality in employment and education) and biological (e.g., higher rates of chronic conditions in females) factors may have contributed to the findings [63].

To facilitate the use of the VR-12 norms, we have created an interactive website (https://​vr12.​cheos.​ubc.​ca/​home). This website includes downloadable comma-separated value files of the health utility score, summary component score, and domain score norms by gender, age group, and province. The website also allows users with respondent-level VR-12 data to calculate VR-12 health utility scores, summary component scores, and domain scores; estimate EQ-5D-5L health utility scores based on a mapping (or ‘crosswalk’) algorithm; and obtain normative VR-12 data for their sample that is adjusted for age, gender, and geographic location.

This study has several strengths and limitations. First, our data come from a large sample of nearly 7000 respondents that were selected to be representative of the Canadian population based on age, gender, and geographic location. To further enhance the representation of our sample we used a raking procedure to weight responses to the 2021 Canadian census and 2017/18 Canadian Community Health Survey based on gender, province, education, age group, and health status. A 2010 study in the US compared online and telephone-based administration for estimating population norms for the PROMIS instrument and found that online administration with post-sampling adjustment resulted in a sample comparable to probability-based general population samples [64]. In our study, adjustment resulted in the sample more closely reflecting the characteristics of the Canadian population, particularly with respect to education and health status, although some imbalances remained. For example, our weighted sample overrepresented those who identify as ‘White’ and underrepresented selected groups, including those who identify as ‘South Asian’ and ‘Black,’ and those in the lowest household gross income bracket. Our sampling procedure, which used an online market research panel, may have resulted in other populations being underrepresented in our sample, such as those without access to a computer or new immigrants. In addition, survey respondents were able to choose to complete the survey in either English or French. Consequently, caution is necessary when generalizing these findings to populations who are underrepresented in our sample or to samples where the VR-12 was administered in one language.

We have estimated Canadian VR-12 population norms for health utility scores, summary component scores, and domain scores in a large, nationally representative population sample. The health utility norms, which are reported by age group, gender, and region, can serve as a valuable input for Canadian economic models, particularly those interested in subgroup analyses. The norms for summary component scores and domain scores provide a reference standard that allows for routinely-collected data to be interpreted in the context of the Canadian population.