Hypertension is the most prevalent chronic non-communicable disease in China , which can lead to serious complications such as cerebral vascular disease, heart disease, heart failure and renal failure. With longer life expectancy in China, there has been an increasing concern on HRQoL of patients with hypertension. This is the first study that employed the EQ-5D scale and Chinese general population-based EQ-5D value set for measurement of HRQoL for adult patients (aged 15 years and above) with hypertension in urban and rural areas, which revealed the current status of HRQoL and its influencing factors for hypertension patients in China.
We found a higher proportion of hypertension patients in the rural area had moderate and extreme problems in the mobility, usual activities, pain/discomfort and anxiety/depression dimensions, as compared with patients in the urban area. This finding agreed with the utility scores of EQ-5D and its each dimension obtained for the urban and rural patients, i.e. the urban patients showed higher utility scores. Studies by Zhou et al. showed that the EQ-5D utility scores of the general population in the urban and rural areas of Shaanxi, China were 0.9569 and 0.9588, respectively. Our study revealed that the hypertension patients in Shaanxi, China had an obviously lower EQ-5D utility score than the general population. Moreover, the proportions of patients reporting moderate problems and extreme problems were also higher than those of the general population in all of the five dimensions [15, 23]. This demonstrated the negative correlation between hypertension and HRQoL. Univariate analysis of the EQ-5D utility scores and categorical variables demonstrated that male hypertension patients had a better HRQoL than female patients. HRQoL of older patients was significantly lower than younger patients, possibly because hypertension is a chronic disease which progresses with age and increasingly affects health. Education level was found to have a significant effect on the health status of hypertension patients, with higher-educated patients having a better HRQoL. There were statistically significant differences in the HRQoL among patients living in Shannan, Guanzhong and Shanbei, which may be related to the different diets in the three regions. Smoking and alcohol consumption were found to be the negative influencing factors of HRQoL, while physical activity was a positive influencing factor.
Tobit regression models further evaluated the effect of multiple factors, and demonstrated that age exerted a significant effect on the HRQoL of hypertension patients. For patients aged 55 years and older, HRQoL decreased significantly with increasing age. Marital status was one of the factors to affect the HRQoL of hypertension patients and married patients showed higher HRQoL than divorced and widowed patients, indicating that the rise of divorce rate would decrease the quality of life of hypertension patients. In both urban and rural areas, HRQoL was positively correlated with education level, and patients with higher education level showed better HRQoL. This was consistent with the findings reported by Zhou et al.  and Andrade et al. , and indicated the importance of improving the overall education level of the population. Employment status also affected the HRQoL of hypertension patients, with employed patients having a significantly better HRQoL than unemployed patients. This finding suggested that solving the employment issue and increasing the employment rate at the national level would contribute to improvement of the quality of life of hypertension patients. In addition, physical activity was a protective factor of HRQoL for urban hypertension patients, indicating that regular exercise was important for improving HRQoL of hypertension patients. In both urban and rural areas, patients who had medical examination in the past one year had a significantly better HRQoL than those who did not. Regular medical examination can not only facilitate early detection and treatment of the complications associated with hypertension, but also improve the patients’ health awareness to prevent the complications and their adoption of a healthy diet and living habit. We suggest that the health administrative departments strengthen the management and monitoring of chronic diseases in the elderly, and further implement the free medical examination program for the elderly under public health programs. Tobit regression model analysis demonstrated that hypertension patients in urban area had a higher HRQoL than those in rural area. This might be caused by the difference of education level, physical activity and medical examination between urban patients and rural patients. Compared with the rural patients, the higher education level, the more regular physical activity and medical examination were the three main reasons for the higher HRQoL of hypertension patients in urban China. Our results are consistent with other studies, demonstrating that hypertension patients in urban area had a higher HRQoL than those in rural area. For example, Pan et al  used the SF-26 scale and showed that the quality of life (QOL) of hypertension patients in cities was significantly higher than patients in rural area. Ma et al  used self-evaluation, mini-mental state examination (MMSE), activities of daily-living (ADL), and center for epidemiologic studies depression scale (CES-D) to study the QOL of older hypertension patients in the Beijing area. They found the quality of life was highly dependent on the residence area and patients in rural area showed lower QOL than patients in the urban area.
This study also has some limitations. First, although the EQ-5D utility scores showed statistically significant difference between the urban and rural hypertension patients, as the minimum clinically important difference (MCID) for the EQ-5D based on the scoring algorithm in China is not estimated yet, we cannot draw a conclusion that difference of EQ-5D utility scores is clinically important. However, as there is a significantly higher proportion of rural patients reported problems in four of five EQ-5D dimensions comparing with urban patients (see Table 2), we can reasonably make the conclusion that the urban hypertension patients might have higher HRQoL than the rural patients in Shaanxi, China, which is also supported by previous studies [25, 26]. Second, there might be some potential individual characteristics affecting HRQoL, which might cause a deviation of the results. Third, this study used cross-sectional survey data to analyze the correlation between HRQoL and the associated factors, rather than the causation. Finally, the data of this study were self-reported and might have some recall bias.