Health is one of the main components of wellbeing in developed societies. World Health Organization defined health broadly about 60 years ago, but life expectancy and mortality have typically been used to define a population's state of health. As medical and public health advances have led to cures and better treatment of diseases, and thereby delayed mortality, it is logical that those who measure health outcomes will begin to assess the population's health not just on the basis of extending life expectancy, but also in terms of improving the quality of life.1 Thus, the concept of health-related quality of life (HRQOL) and its determinants has evolved over the last 40 years. Some authors have described HRQOL as the outcome of the interaction of variables across four levels: biological and psychological factors, symptoms, functioning (psychologically and socially), and general health perception.2 HRQOL has been defined as the individual's perception of their position in life in the context of the culture and value systems they live in, and in relation to their goals, expectations, standards, and concerns. It is a broad ranging concept affected in a complex way by the person's physical health, psychological state, level of independence, social relationships, and their relationship to salient features of their environment.3

Measuring HRQOL can help summarise the patient's experience of illness, and therefore characterise the social burden of chronic disease. Assessing HRQOL and its distribution across populations will help monitor our progress in achieving population health objectives, therefore contributing to reduce health inequalities between individuals, communities, and regions in our society through greater improvements in more disadvantaged communities.4 Understanding relationships among the HRQOL components will allow for designing more effective public health interventions.5

HRQOL determinants have been broadly studied. Numerous studies have demonstrated the association between physical,6 psychological,7 and social determinants and changes in HRQOL perception.8,9 Individuals with better functioning capacity, social support,10,11 socioeconomic status,12,13 and psychological condition14 display superior perception of HRQOL. Self-perceived HRQOL has also been related to lifestyle factors, such as being physically active;15,16 in contrast, it has been found to be inversely correlated with negative conditions, such as obesity.17

In the Spanish population, HRQOL has been described in detail, and differences in HRQOL by regions have been reported,18,19 although the extent of the influence of personal and environmental factors on HRQOL perception is unclear. Understanding these relationships can be of great interest in planning interventions to improve health outcomes and elucidating the reasons for certain outcomes. This study sought to identify the burden of several determinants on HRQOL, measured via the EQ-5D-5L, in the Spanish population, and to assess the potential HRQOL heterogeneity among the different Spanish regions.

Of the 21,007 subjects aged >15 years who answered the questionnaire concerning HRQOL, 20,979 did so in a way in which utility scores could be obtained. Of these, 62.4% (95%CI: 61.8%–63.2%) expressed a utility score of 1. Of the entire sample, 20,821 subjects reported their health condition using the EQ-VAS, 54.2% of whom (95%CI: 53.5%–54.9%) reported a score of ≥80.

Table 1 shows the distributions of variables and the number of subjects from whom they were obtained.

Table 2 shows how the incorporation of additional covariates improved the fit of the models to the HRQOL data. Demographic variables contributed significantly to explaining the variability in responses, and so did disease-related variables. Social variables were strongly correlated with HRQOL perception but did not improve the model, and even reduced the R2. The variable accounting for mental health improved the model adjustment. Variables related to lifestyle (physical activity and BMI) were also associated with HRQOL, but did not improve the global capacity of the model. Alcohol consumption and smoking habit were not included in model 5, since their coefficients were negligible and worsened the model's fit.

In Table 3, the best models are shown in detail. Female sex was associated with a reduction in HRQOL measured in utilities (−0.017 points). Each 10-year increase in age was associated with a decrease of 0.020 points in utilities, and 2.420 points on the EQ-VAS. Age squared coefficients were tested in the model, but did not achieve a better fit.

Experiencing a chronic condition, severe limitations for the preceding 2 weeks, and chronic limitation for the preceding 6 months were also associated with a perception of poorer quality of life, with severe limitations experienced for the preceding 6 months exerting the greatest effect. These limitations caused average reductions of 0.373 points in utilities and 17.867 points on the EQ-VAS.

Disadvantaged social classes were associated with poorer perceived HRQOL, measured using both the utility index and the EQ-VAS, and a gradient was observed indicating that the lower the social class, the poorer the HRQOL reported. Differences of 0.016 points in utilities were observed between social classes I and VI. Similarly, every two standard deviations (15.0 points) increase in the social support score was related to a decrease of 0.003 points in utilities and 1.397 points on the EQ-VAS.

The association between Goldberg's test score and HRQOL was negative. Every two standard deviations (5.52 points) increase in Goldberg's score was associated with a decrease of 0.041 points in utilities and 8.234 points on the EQ-VAS. The relationship between BMI and HRQOL was only evident when comparing obesity with normal weight (−0.012 points in utilities and −1.911 on the EQ-VAS). Physical activity was related with improved HRQOL. Individuals who engaged in physical activity several times per week had increases of 0.026 points in utilities and 3.975 points on the EQ-VAS compared to those not performing any physical activity.

Models for subjects older and younger than 50 years of age were built, but no significant differences were observed between their coefficients; therefore, only general models are presented.

Figure 1 shows the distribution of the gross residuals for the utility values in each region (the non-explained variability). Figure 2 shows the residuals for the EQ-VAS model. No significant differences were found between different regions once the adjusted predicted values were subtracted from the expressed values. The ICC was 0.004 for the utility residuals and 0.020 for the EQ-VAS score residuals, which implies that 0.4% and 2%, respectively, of the variability of the residuals was due to the effect of regional aggregation.

Figure 1.

Distribution of the residuals for the predicted utilities in the different regions in Spain.

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Figure 2.

Distribution of the residuals for the Visual Analogue Scale scores in the different regions in Spain.

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HRQOL perception in the Spanish population varied slightly depending on the measure used (utility index or EQ-VAS). HRQOL was strongly related to age, mental health, and the presence of limitations in daily life activities, particularly in the case of long-term limitations. Social class was positively correlated with HRQOL, as were certain health behaviours such as being physically active or maintaining a normal weight. These results are not surprising as these factors have been found to be related to HRQOL in other studies;11,14,29 however, the way in which emotions, mental distress, social problems, and physical illness are perceived, experienced, and expressed are dependent on culture and environment.30 Therefore, we found it valuable to study the distribution and relative weight of determinants of HRQOL in the Spanish population in a comprehensive way. Additionally, the findings suggest that previously reported differences in HRQOL by regions were due to differences in the population characteristics rather than contextual effects.

Sociodemographic characteristics, especially ageing, were strongly related to HRQOL, although health expectations have been hypothesised to be readjusted throughout life.31 Contrary to other studies,32 we did not find differences in the factors that impact HRQOL between people under or over 50 years of age, suggesting that ageing worsened perceived HRQOL, but did not influence its determinants. Previously observed differences in HRQOL33 by sex were only noted when utility indexes were used, and could be influenced by social determinants and lifestyle, particularly in older individuals.34

Variables related to social class12,13 and social support10,11 have been shown to greatly influence differences in HRQOL. It has been reported that more generous welfare regimes experience lesser socioeconomic inequalities in their quality of life.9 Hence the relative importance of social class and how one's perception of social support is associated with perceived HRQOL, which could be studied in future research in the context of our welfare system's strength.

The influence of factors related to chronic disease in explaining HRQOL is well known,35 but this study emphasizes the role of perceived limitations to shape the relationship between disease and HRQOL,6 and the findings suggest that interventions addressing limitations can provide significant health benefits.36

Mental health condition has been found to have a strong association with reported HRQOL.14 The negative effect of a poor mental condition on the individual's HRQOL has been previously reported in the Spanish population, suggesting the need for global policies aimed at reducing this burden.7 These results highlight the fact that mental health status can be as relevant as age and chronic limitations in explaining differences in reported HRQOL in the Spanish population.

Regarding the role of health-related behaviours, alcohol and tobacco consumption did not showed a clear association with reported HRQOL. The relationship between alcohol consumption and HRQOL has been difficult to model,37 and smoking has been related to a worse perception of HRQOL,38 but it is possible that people with poorer health are recommended to cease these habits; therefore, expected associations are spurious or do not occur. Better HRQOL was observed in those who referred any physical activity in their leisure time as opposed to those with no physical activity, after adjusting for other determinants of HRQOL, which is relevant because moderate increase of physical activity has been shown to produce improvements in HRQOL.39

Obesity has been described as a factor associated with higher morbidity and poorer HRQOL.17 In this study, overweight subjects showed a slightly higher HRQOL than normal weight subjects, measured by utility score but not when using the VAS scale. Robust differences in HRQOL were only found between obese and normal-weight subjects, as other studies reported.40

Research on health-related contextual effects has been performed, maybe spurred by an increasing interest in macro-social influences on the individual's health status. The research has mainly focused on the relationship between spatially concentrated deprivation and health, but empirical findings are controversial and depend on the studied aggregation level.41 Significant differences in expressed HRQOL by regions has been described in Spain,19 as well as in other countries.11,42,43 Differences in the effect of context on HRQOL have also been reported in the Spanish population.29 In contrast to these works, we studied a larger body of variables related to HRQOL, such as social class and, perhaps even more importantly, perceived limitations, which yielded negligible differences among regions. This suggests that differences could mainly be due to compositional differences among region populations rather than contextual effects, which could explain the differences in reported HRQOL. As with other studies, the relatively large size of the included administrative area can hinder the detection of any significant contextual effect related to HRQOL at those regional levels,44 but these findings are relevant in the Spanish health setting since services are designed at that specific level. Reported differences in HRQOL could lead to change normative values of HRQOL tests,42 or to strengthen public health policies in disadvantaged regions 43. In Spain, interventions to improve HRQOL should be tailored for different target populations according to age, impairment, mental health status, or social class, but not different regions.

This study was subject to design limitations. First, its cross-sectional design limits the possibility to establish causal relationships. Therefore, the absence of an association between tobacco or alcohol consumption and HRQOL could be a consequence of disease or the actions of health agents. Another limitation is that some data were self-reported, and a certain bias of indulgence might be present. Additionally, tariffs for EQ-5D-5L were estimated from the cross-walk index from the Spanish tariffs, an approach with several limitations, like placing an artificial floor effect on the values of the 5L, when the EQ-5D-3L is used for comparison.22 On the other hand, there is a current debate on whether censoring regression methods are appropriate to make estimations over the censored part of the variables, as previous anchor measures for the utilities and VAS should not be used.45

Regarding the strengths of the study, the survey methodology poses the best approximation of the Spanish population's health at present, and the methodology used in the analysis fits the particularity of the sampling method.

This study has several implications. It must be noted that when assessing the effect of a disease on HRQOL in the Spanish population, its impact is better explained by the impairment or emotional burden rather than the presence of the disease itself. Hence, interventions to improve HRQOL must act on the components that result in limitations in daily activities and the agents that affect mental health, a valid approach for any age range. Promoting physical activity, especially for those who do not engage in leisure physical activity, and interventions aimed at preventing obesity could also be helpful for the maintenance of good HRQOL perception. On the other hand, HRQOL can be a useful measure to identify health inequalities among individuals and communities, and this study highlights the importance of taking social class into consideration when public health interventions are being planned. However, in order to study differences in HRQOL by regions, identifying compositional effects is necessary before attributing these differences to contextual covariates.

In summary, and given the relevance of HRQOL for a population's health, the findings of this study can allow for identifying subgroups which should be specifically targeted, like the elderly or those belonging to the least favoured classes, and to set priorities for effective public health interventions, especially promoting physical activity or healthy ageing, early interventions to limit impairment or chronic conditions, and mental health strategies.

Maria-Victoria Zunzunegui.

The corresponding author on behalf of the other authors guarantee the accuracy, transparency and honesty of the data and information contained in the study, that no relevant information has been omitted and that all discrepancies between authors have been adequately resolved and described.

J. Martín-Fernández, I. del Cura-González and A. Sarria-Santamera conceived the idea and designed the study. J. Martín-Fernández and I. del Cura-González got the cleaned and annotated database. J. Martín-Fernández, G. Ariza-Cardiel, E. Polentinos-Castro and T. Sanz-Cuesta developed the statistical analysis and discussed the preliminary results. J. Martín-Fernández, G. Ariza-Cardiel, E. Polentinos-Castro, T. Sanz-Cuesta, A. Sarria-Santamera and I. del Cura-González studied the meaning of the results and their health policy implications. All authors have discussed and approved the submitted manuscript.

This manuscript has been translated and edited with the support of ISCIII and FEDER Funds, Grant Number RD12/0001/0012. Publication charges have been supported by ISCIII, grant Number 1300648.

None.