The influence of parents' and partner's education on own health behaviours.

The link between educational attainment and multiple health behaviours has been explained in various ways. This paper provides new insights into the social patterning in health behaviours by investigating the influence of parents' and partners' educational attainments on a composite indicator that integrates the four commonly studied lifestyle behaviours (smoking, alcohol, physical activity and BMI). Two key outcome indicators of interests were created to reflect both ends of the "healthy - unhealthy spectrum". Data was drawn from The Tromsø Study, conducted in 2015/16 (N = 21,083, aged 40-93 years). We controlled for two indicators of early life human capital and one personality trait variable. Partners' education attainments are relatively more important for avoiding unhealthy behaviour than choosing healthy behaviour; on the contrary, parents' education is more important for healthy behaviour. Heterogeneity by sex and age was also evident. The influences of partner's education on widening the socioeconomic contrasts in health behaviours were much stronger in the younger (40-59 years) age group. In conclusion, our results support the hypothesis that own health behaviour is affected by the educational attainments of our 'nearest and dearest' (i.e. spouse, mother, and father), net of own education. This study facilitates a better understanding of education-health behaviours nexus from a life course perspective and supports the importance of family-based interventions to improve healthy behaviours.

The relative importance of education and health behaviour for health and wellbeing.

BACKGROUND: Indicators of socioeconomic position (SEP) and health behaviours (HB) are widely used predictors of health variations. Their relative importance is hard to establish, because HB takes a mediating role in the link between SEP and health. We aim to provide new knowledge on how SEP and HB are related to health and wellbeing. METHODS: The analysis considered 14,713 Norwegians aged 40-63. Separate regressions were performed using two outcomes for health-related quality of life (EQ-5D-5 L; EQ-VAS), and one for subjective wellbeing (Satisfaction with Life Scale). As predictors, we used educational attainment and a composite measure of HB - both categorized into four levels. We adjusted for differences in childhood financial circumstances, sex and age. We estimated the percentage share of each predictor in total explained variation, and the relative contributions of HB in the education-health association. RESULTS: The reference case model, excluding HB, suggests consistent stepwise education gradients in health-related quality of life. The gap between the lowest and highest education was 0.042 on the EQ-5D-5 L, and 0.062 on the EQ-VAS. When including HB, the education effects were much attenuated, making HB take the lion share of the explained health variance. HB contributes 29% of the education-health gradient when health is measured by EQ-5D-5 L, and 40% when measured by EQ-VAS. For subjective wellbeing, we observed a strong HB-gradient, but no education gradient. CONCLUSION: In the institutional context of a rich egalitarian country, variations in health and wellbeing are to a larger extent explained by health behaviours than educational attainment.

Amplified disparities: The association between spousal education and own health.

Positive associations between own educational attainment and own health have been extensively documented. Studies have also shown spousal educational attainment to be associated with own health. This paper investigates the extent to which spousal education contributes to the social gradient in health, net of own education; and whether parts of a seeming spousal education effect are attributable to differences in early-life human capital, as measured by respondents' height and childhood living standard. Furthermore, we investigate the relative contribution of predictors in the regression analysis by use of Shapley value decomposition. We use data from a comprehensive health survey from Northern Norway (conducted in 2015/16, N = 21,083, aged 40 and above). We apply three alternative health outcome measures: the EQ-5D-5L index, a visual analogue scale (EQ-VAS) and self-rated health. In all models considered, spousal education is generally positively significant for both men and women. The results also suggest that spousal education is generally more important for men than women. In the sub-sample of individuals having a spouse, decomposition analyses showed that the relative contribution of spousal education to the goodness-of-fit in men's (women's) health was 13% (14%) with the EQ-5D-5L; 25% (20%) with the EQ-VAS and; 30% (21%) with self-rated health. Heterogeneity analyses showed stronger spousal education effects in younger age groups. In conclusion, we have provided empirical evidence that spousal education may contribute to explaining the amplified health gradient in an egalitarian country like Norway.

Is amalgam removal in patients with medically unexplained physical symptoms cost-effective? A prospective cohort and decision modelling study in Norway.

There are many patients in general practice with health complaints that cannot be medically explained. Some of these patients attribute their health complaints to dental amalgam restorations. This study examined the cost-effectiveness of the removal of amalgam restorations in patients with medically unexplained physical symptoms (MUPS) attributed to amalgam fillings compared to usual care, based on a prospective cohort study in Norway. Costs were determined using a micro-costing approach at the individual level. Health outcomes were documented at baseline and approximately two years later for both the intervention and the usual care using EQ-5D-5L. Quality adjusted life year (QALY) was used as a main outcome measure. A decision analytical model was developed to estimate the incremental cost-effectiveness of the intervention. Both probabilistic and one-way sensitivity analyses were conducted to assess the impact of uncertainty in costs and effectiveness. In patients who attribute health complaints to dental amalgam restorations and fulfil the inclusion and exclusion criteria, amalgam removal is associated with modest increase in costs at societal level as well as improved health outcomes. In the base-case analysis, the mean incremental cost per patient in the amalgam group was NOK 19 416 compared to the MUPS group, while mean incremental QALY was 0.119 with a time horizon of two years. Thus, the incremental costs per QALY of the intervention was NOK 162 680, which is usually considered cost effective in Norway. The estimated incremental cost per QALY decreased with increasing time horizon, and amalgam removal was found to be cost saving over both 5 and 10 years. This study provides insight into the costs and health outcomes associated with the removal of amalgam restorations in patients who attribute health complaints to dental amalgam fillings, which are appropriate instruments to inform health care priorities.

Validity and responsiveness of GHC-index in patients with amalgam-attributed health complaints.

OBJECTIVE: Many patients have medically unexplained physical symptoms (MUPS); some of them attribute their health complaints to dental amalgam fillings. The aim of this study was to assess the validity and responsiveness of General Health Complaints index (GHC-index) for measuring the symptom load in MUPS patients compared to the widely used symptom outcome measure, Giessen Subjective Complaints List (GBB-24). METHODS: Three outcome measures - GHC-index, GBB-24, and Munich Amalgam Scale (MAS) - were administered at baseline and 12 months after removal of all dental amalgam restorations. The validity and responsiveness of these symptom measures were tested against external anchors: bodily distress syndrome (BDS), SF-36 vitality, and visual analogue scale (VAS). We tested both convergent and known group validities. We also examined the predictive validity and responsiveness to changes for each instrument. RESULTS: All the main outcome measures showed evidence of convergent and known group validities. The GHC-index, GBB-24 and MAS were all able to detect the anticipated differences in BDS and Energy. But the GBB-24 was more efficient in discriminating the BDS compared with the GHC-index (relative efficiency: RE = 0.69; 95% CI: 0.41-0.96) and MAS (RE = 0.59; 95% CI: 0.32-0.86). Each main outcome variable revealed good predictive validity for vitality (standardized coefficient: b ≈ 0.71 and R2 ≈ 0.50). Moderate to high sensitivity to change over time was demonstrated, with GHC-index performing better. CONCLUSION: The GHC-index is a valid and responsive instrument for assessing symptom load in MUPS patients attributing their health complaints to amalgam fillings and undergoing amalgam removal.

Cycle-network expansion plan in Oslo: Modeling cost-effectiveness analysis and health equity impact.

Physical inactivity is the leading cause of non-communicable diseases, and further research on the cost-effectiveness of interventions that target inactivity is warranted. Socioeconomic status is vital in this process. We aim to evaluate the cost-effectiveness of a cycle-network expansion plan in Oslo compared to the status quo by income quintiles. We applied a Markov model using a public payer perspective. Health outcomes were measured by quality-adjusted life years (QALYs) gained from the prevention of coronary heart disease, stroke, type 2 diabetes, and cancer. We measured equity impact by the concentration index and social welfare using the achievement index. We conducted sensitivity analyses. The intervention was generally more costly and more effective than the status quo. Incremental cost per QALY falls with income quintile, ranging from $10,098 in the richest quintile to $23,053 per QALY gained in the poorest quintile. The base-case intervention increased health inequality. However, a scenario targeting low-income quintiles reduced inequality and increased social welfare. In conclusion, the cycle-network expansion is likely to be cost-effective, but with equity concerns. If decision makers care about health inequalities, the disadvantaged groups could be targeted to produce more equitable and socially desirable outcomes instead of a uniform intervention across income quintiles.

Validity and responsiveness of EQ-5D-5L and SF-6D in patients with health complaints attributed to their amalgam fillings: a prospective cohort study of patients undergoing amalgam removal.

BACKGROUND: Evidence of health utility changes in patients who suffer from longstanding health complaints attributed to dental amalgam fillings are limited. The change in health utility outcomes enables calculating quality-adjusted life-year (QALY) and facilitates the comparison with other health conditions. The purpose of this study was to estimate the validity and responsiveness of the EQ-5D-5L and SF-6D utilities following removal of dental amalgam fillings in patients with health complaints attributed to their amalgam fillings, and examine the ability of these instruments to detect minimally important changes over time. METHODS: Patients with medically unexplained physical symptoms, which they attributed to dental amalgam restorations, were recruited to a prospective cohort study in Norway. Two health state utility instruments, EQ-5D-5L and SF-6D, as well as self-reported general health complaints (GHC-index) and visual analogue scale (EQ-VAS) were administered to all patients (n = 32) at baseline and at follow-up. The last two were used as criteria measures. Concurrent and predictive validities were examined using correlation coefficients. Responsiveness was assessed by the effect size (ES), standardized response mean (SRM), and relative efficiency. Minimally important change (MIC) was examined by distribution and anchor-based approaches. RESULTS: Concurrent validity of the EQ-5D-5L was similar to that of SF-6D utility. EQ-5D-5L was more responsive than SF-6D: the ES were 0.73 and 0.58 for EQ-5D-5L and SF-6D, respectively; SRM were 0.76 and 0.67, respectively. EQ-5D-5L was more efficient than SF-6D in detecting changes, but both were less efficient compared to criteria-based measures. The estimated MIC of EQ-5D-5L value set was 0.108 and 0.118 based on distribution and anchor-based approaches, respectively. The corresponding values for SF-6D were 0.048 and 0.064, respectively. CONCLUSIONS: In patients with health complaints attributed to dental amalgam undergoing amalgam removal, both EQ-5D-5L and SF-6D showed reasonable concurrent and predictive validity and acceptable responsiveness. The EQ-5D-5L utility appears to be more responsive compared to SF-6D. Trial registration The research was registered at ClinicalTrials.gov., NCT01682278. Registered 10 September 2012, https://clinicaltrials.gov/ct2/show/NCT01682278 .

Is cycle network expansion cost-effective? A health economic evaluation of cycling in Oslo.

BACKGROUND: Expansion of designated cycling networks increases cycling for transport that, in turn, increases physical activity, contributing to improvement in public health. This paper aims to determine whether cycle-network construction in a large city is cost-effective when compared to the status-quo. We developed a cycle-network investment model (CIM) for Oslo and explored its impact on overall health and wellbeing resulting from the increased physical activity. METHODS: First, we applied a regression technique on cycling data from 123 major European cities to model the effect of additional cycle-networks on the share of cyclists. Second, we used a Markov model to capture health benefits from increased cycling for people starting to ride cycle at the age of 30 over the next 25 years. All health gains were measured in quality-adjusted life years (QALYs). Costs were estimated in US dollars. Other data to populate the model were derived from a comprehensive literature search of epidemiological and economic evaluation studies. Uncertainty was assessed using deterministic and probabilistic sensitivity analyses. RESULTS: Our regression analysis reveals that a 100 km new cycle network construction in Oslo city would increase cycling share by 3%. Under the base-case assumptions, where the benefits of the cycle-network investment relating to increased physical activity are sustained over 25 years, the predicted average increases in costs and QALYs per person are $416 and 0.019, respectively. Thus, the incremental costs are $22,350 per QALY gained. This is considered highly cost-effective in a Norwegian setting. CONCLUSIONS: The results support the use of CIM as part of a public health program to improve physical activity and consequently avert morbidity and mortality. CIM is affordable and has a long-term effect on physical activity that in turn has a positive impact on health improvement.

Does linear equating improve prediction in mapping? Crosswalking MacNew onto EQ-5D-5L value sets.

PURPOSE: Preference-based measures are essential for producing quality-adjusted life years (QALYs) that are widely used for economic evaluations. In the absence of such measures, mapping algorithms can be applied to estimate utilities from disease-specific measures. This paper aims to develop mapping algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and the English and the US-based EQ-5D-5L value sets. METHODS: Individuals with heart disease were recruited from six countries: Australia, Canada, Germany, Norway, UK and the US in 2011/12. Both parametric and non-parametric statistical techniques were applied to estimate mapping algorithms that predict utilities for MacNew scores from EQ-5D-5L value sets. The optimal algorithm for each country-specific value set was primarily selected based on root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), and r-squared. Leave-one-out cross-validation was conducted to test the generalizability of each model. RESULTS: For both the English and the US value sets, the one-inflated beta regression model consistently performed best in terms of all criteria. Similar results were observed for the cross-validation results. The preferred model explained 59 and 60% for the English and the US value set, respectively. Linear equating provided predicted values that were equivalent to observed values. CONCLUSIONS: The preferred mapping function enables to predict utilities for MacNew data from the EQ-5D-5L value sets recently developed in England and the US with better accuracy. This allows studies, which have included the MacNew to be used in cost-utility analyses and thus, the comparison of services with interventions across the health system.

Does the EQ-5D usual activities dimension measure what it intends to measure? The relative importance of work, study, housework, family or leisure activities.

BACKGROUND: The EQ-5D is the most widely used generic preference-based health-related quality of life measure. It comprises five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. The usual activities dimension asks respondents to evaluate the severity of problems in their usual activities, such as work, study, housework, family or leisure activities. The primary aim of this study is to investigate whether the EQ-5D (five-level) usual activities dimension captures those activities that it intends to capture. We further assess the relative importance of each of these activities for the usual activities dimension. METHODS: Data include 7933 respondents from six countries: Australia, Canada, Germany, Norway, the UK, and the US. Logistic regression and ordinary least square regression models investigate the relationship between the usual activities dimension and its main predictors (work/study, housework, family, and leisure activities). A Shapley value decomposition method was applied to measure the relative importance of each predictor. RESULTS: Work/study, housework, family, and leisure activities were all significant (p < 0.001) determinants of usual activities dimension. The respective marginal contribution (in %) of housework, leisure, work/study and family to UA dimension (as a share of goodness-of-fit) is 28.0, 26.2, 20.8 and 14.7 in the logistic regression model. This finding is consistent when linear regression is used as an alternative model. CONCLUSIONS: The usual activities dimension in EQ-5D reflects the specific activities described to respondents. Therefore, the usual activities dimension measures what it really intends to measure.

Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D.

PURPOSE: The purpose of the study was to compare alternative statistical techniques to find the best approach for converting QLQ-C30 scores onto EQ-5D-5L and SF-6D utilities, and to estimate the mapping algorithms that best predict these health state utilities. METHODS: 772 cancer patients described their health along the cancer-specific instrument (QLQ-C30) and two generic preference-based instruments (EQ-5D-5L and SF-6D). Seven alternative regression models were applied: ordinary least squares, generalized linear model, extended estimating equations (EEE), fractional regression model, beta binomial (BB) regression, logistic quantile regression and censored least absolute deviation. Normalized mean absolute error (NMAE), normalized root mean square error (NRMSE), r-squared (r2) and concordance correlation coefficient (CCC) were used as model performance criteria. Cross-validation was conducted by randomly splitting internal dataset into two equally sized groups to test the generalizability of each model. RESULTS: In predicting EQ-5D-5L utilities, the BB regression performed best. It gave better predictive accuracy in terms of all criteria in the full sample, as well as in the validation sample. In predicting SF-6D, the EEE performed best. It outperformed in all criteria: NRMSE = 0.1004, NMAE = 0.0798, CCC = 0.842 and r2 = 72.7% in the full sample, and NRMSE = 0.1037, NMAE = 0.0821, CCC = 0.8345 and r2 = 71.4% in cross-validation. CONCLUSIONS: When only QLQ-C30 data are available, mapping provides an alternative approach to obtain health state utility data for use in cost-effectiveness analyses. Among seven alternative regression models, the BB and the EEE gave the most accurate predictions for EQ-5D-5L and SF-6D, respectively.

Assessment of outcome measures for cost-utility analysis in depression: mapping depression scales onto the EQ-5D-5L.

BACKGROUND: Many clinical studies including mental health interventions do not use a health state utility instrument, which is essential for producing quality-adjusted life years. In the absence of such utility instrument, mapping algorithms can be applied to estimate utilities from a disease-specific instrument.AimsWe aim to develop mapping algorithms from two widely used depression scales; the Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K-10), onto the most widely used health state utility instrument, the EQ-5D-5L, using eight country-specific value sets. METHOD: A total of 917 respondents with self-reported depression were recruited to describe their health on the DASS-21 and the K-10 as well as the new five-level version of the EQ-5D, referred to as the EQ-5D-5L. Six regression models were used: ordinary least squares regression, generalised linear models, beta binomial regression, fractional logistic regression model, MM-estimation and censored least absolute deviation. Root mean square error, mean absolute error and r2 were used as model performance criteria to select the optimal mapping function for each country-specific value set. RESULTS: Fractional logistic regression model was generally preferred in predicting EQ-5D-5L utilities from both DASS-21 and K-10. The only exception was the Japanese value set, where the beta binomial regression performed best. CONCLUSIONS: Mapping algorithms can adequately predict EQ-5D-5L utilities from scores on DASS-21 and K-10. This enables disease-specific data from clinical trials to be applied for estimating outcomes in terms of quality-adjusted life years for use in economic evaluations.Declaration of interestNone.

Do country-specific preference weights matter in the choice of mapping algorithms? The case of mapping the Diabetes-39 onto eight country-specific EQ-5D-5L value sets.

PURPOSE: To develop mapping algorithms that transform Diabetes-39 (D-39) scores onto EQ-5D-5L utility values for each of eight recently published country-specific EQ-5D-5L value sets, and to compare mapping functions across the EQ-5D-5L value sets. METHODS: Data include 924 individuals with self-reported diabetes from six countries. The D-39 dimensions, age and gender were used as potential predictors for EQ-5D-5L utilities, which were scored using value sets from eight countries (England, Netherland, Spain, Canada, Uruguay, China, Japan and Korea). Ordinary least squares, generalised linear model, beta binomial regression, fractional regression, MM estimation and censored least absolute deviation were used to estimate the mapping algorithms. The optimal algorithm for each country-specific value set was primarily selected based on normalised root mean square error (NRMSE), normalised mean absolute error (NMAE) and adjusted-r2. Cross-validation with fivefold approach was conducted to test the generalizability of each model. RESULTS: The fractional regression model with loglog as a link function consistently performed best in all country-specific value sets. For instance, the NRMSE (0.1282) and NMAE (0.0914) were the lowest, while adjusted-r2 was the highest (52.5%) when the English value set was considered. Among D-39 dimensions, the energy and mobility was the only one that was consistently significant for all models. CONCLUSIONS: The D-39 can be mapped onto the EQ-5D-5L utilities with good predictive accuracy. The fractional regression model, which is appropriate for handling bounded outcomes, outperformed other candidate methods in all country-specific value sets. However, the regression coefficients differed reflecting preference heterogeneity across countries.

In search of a common currency: A comparison of seven EQ-5D-5L value sets.

The recently published EQ-5D-5L value sets from Canada, England, Japan, Korea, the Netherlands, Spain, and Uruguay are compared with an aim to identify any similarities in preference pattern. We identify some striking similarities for Canada, England, the Netherlands, and Spain in terms of (a) the relative importance of the 5 dimensions; (b) the relative utility decrements across the 5 levels; and (c) the scale length. On the basis of the observed similarities across these 4 Western countries, we develop an amalgam model, WePP (western preference pattern), and compare it with these 4 value sets. The values generated by this model show a high degree of concordance with those of England, Canada, and Spain. Patient level data were obtained from the Multi-Instrument Comparison project, which includes participants from 6 countries in 7 disease groups (N = 7,933): The WePP values lie within the confidence intervals for the value sets in Canada, England, and Spain across the whole severity distribution. We suggest that the WePP model represents a useful "common currency" for (Western) countries that have not yet developed their own value sets. Further research is needed to disentangle the differences between value sets due to preference heterogeneity from those stemming from methodological differences.

Yes, health is important, but as much for its importance via social life: The direct and indirect effects of health on subjective well-being in chronically ill individuals.

There is an increasing evidence that health-related quality of life, income, and social relationships are important to our subjective well-being (SWB). Little is known, however, about the specific indirect pathways that link health to SWB via social relationships and income. On the basis of a unique data set of 7 disease groups from 6 OECD-countries (N = 6,173), we investigate the direct and indirect effects of health on SWB by using structural equation modeling. Three alternative measures of health are used: For generic instruments (EQ-5D-5L; SF-6D), the total indirect effect was stronger (0.226; 0.249) than its direct effect (0.157; 0.205). For the visual analogue scale, the direct effect was stronger (0.322) than its total indirect effect (0.179). Most of the indirect effect of improved health on SWB transmitted through social relationships. The effect via income was small. Nevertheless, the presence of unmeasured confounders may bias the estimates. An important lesson for researchers is to include meaningful items on social relationships when measuring the benefits from improved health. An important lesson for policy makers is that social isolation appears to be more detrimental to overall well-being than ill health. Hence, the Health and Care Services should facilitate social arenas for people with chronic conditions.

Preference Weighting of Health State Values: What Difference Does It Make, and Why?

BACKGROUND: Most patient-reported outcome measures apply a simple summary score to assess health-related quality of life, whereby equal weight is normally assigned to each item. In the generic preference-based instruments, utility weighting is essential whereby health state values are estimated through preference elicitation and complex algorithms. OBJECTIVES: To examine the extent to which preference-weighted value sets differ from unweighted values in the five-level EuroQol five-dimensional questionnaire and the 15D instrument, on the basis of a comprehensive data set from six member countries of the Organisation for Economic Co-operation and Development, each with a representative healthy sample and seven disease groups (N = 7933). METHODS: Construct validities were examined. The level of agreement between preference-weighted and unweighted values was also assessed using intraclass correlation coefficient (ICC), Bland-Altman plots, and reduced major axis regression. RESULTS: The performances of preference-weighted and unweighted measures were comparable with regard to convergent and known-group validities for each instrument. Although unweighted values in the five-level EuroQol five-dimensional questionnaire differ considerably from the preference-weighted values at the individual level, the discrepancy is minimal at the group level with a mean difference of 0.023. The ICC (0.96) and the Bland-Altman plot also suggest strong overall agreement. For the 15D, both the ICC (0.99) and the Bland-Altman plot revealed almost perfect agreement, with a negligible mean difference of -0.001. Results from the reduced major axis regression also showed small bias. CONCLUSIONS: Overall, preference weighting has minimal effect if the unweighted values are anchored on the same scale as the preference-weighted value sets.

The relative importance of health, income and social relations for subjective well-being: An integrative analysis.

There is much evidence that health, income and social relationships are important for our well-being, but little evidence on their relative importance. This study makes an integrative analysis of the relative influence of health related quality of life (HRQoL), household income and social relationships for subjective well-being (SWB), where SWB is measured by the first three of the five items on the satisfaction with life scale (SWLS). In a comprehensive 2012 survey from six countries, seven disease groups and representative healthy samples (N = 7933) reported their health along several measures of HRQoL. A Shapley value decomposition method measures the relative importance of health, income and social relationships, while a quantile regression model tests how the effects of each of the three predictors vary across different points of SWB distributions. Results are compared with the standard regression. The respective marginal contribution of social relationships, health and income to SWB (as a share of goodness-of-fit) is 50.2, 19.3 and 7.3% when EQ-5D-5L is used as a measure of health. These findings are consistent across models based on five alternative measures of HRQoL. The influence of the key determinants varied significantly between low and high levels of the SWB distribution, with health and income having stronger influence among those with relatively lower SWB. Consistent with several studies, income has a significantly positive association with SWB, but with diminishing importance.

Health state utility instruments compared: inquiring into nonlinearity across EQ-5D-5L, SF-6D, HUI-3 and 15D.

PURPOSE: Different health state utility (HSU) instruments produce different utilities for the same individuals, thereby compromising the intended comparability of economic evaluations of health care interventions. When developing crosswalks, previous studies have indicated nonlinear relationships. This paper inquires into the degree of nonlinearity across the four most widely used HSU-instruments and proposes exchange rates that differ depending on the severity levels of the health state utility scale. METHODS: Overall, 7933 respondents from six countries, 1760 in a non-diagnosed healthy group and 6173 in seven disease groups, reported their health states using four different instruments: EQ-5D-5L, SF-6D, HUI-3 and 15D. Quantile regressions investigate the degree of nonlinear relationships between these instruments. To compare the instruments across different disease severities, we split the health state utility scale into utility intervals with 0.2 successive decrements in utility starting from perfect health at 1.00. Exchange rates (ERs) are calculated as the mean utility difference between two utility intervals on one HSU-instrument divided by the difference in mean utility on another HSU-instrument. RESULTS: Quantile regressions reveal significant nonlinear relationships across all four HSU-instruments. The degrees of nonlinearities differ, with a maximum degree of difference in the coefficients along the health state utility scale of 3.34 when SF-6D is regressed on EQ-5D. At the lower end of the health state utility scale, the exchange rate from SF-6D to EQ-5D is 2.11, whilst at the upper end it is 0.38. CONCLUSION: Comparisons at different utility levels illustrate the fallacy of using linear functions as crosswalks between HSU-instruments. The existence of nonlinear relationships between different HSU-instruments suggests that level-specific exchange rates should be used when converting a change in utility on the instrument used, onto a corresponding utility change had another instrument been used. Accounting for nonlinearities will increase the validity of the comparison for decision makers when faced with a choice between interventions whose calculations of QALY gains have been based on different HSU-instruments.