Abstract
The aim of our study was to investigate the effect of hypertension on health-related quality of life (HRQoL) among different age subgroups of people in Shanghai using subpopulation treatment effect pattern plot (STEPP) methodology. We utilized data from the fifth Health Service Survey of Shanghai, 2013, which utilizes a cross-sectional study design. The participants were selected into the survey by using a three-stage, stratified, random sampling method. HRQoL was evaluated by the EuroQol five-dimensional 3 level (EQ-5D-3L) questionnaire, and the EuroQol-visual analog scales (EQ-VAS) score was the main outcome. A generalized estimating equations (GEE) model adjusted for socio-demographic covariates was used to determine the effect of hypertension on HRQoL. STEPP analysis was performed to explore the effect of hypertension within overlapping age subpopulations. Subgroup analyses for gender were conducted for the main outcome. A total of 28,730 residents who were 18 years or older were included in our study. The results of the multivariate GEE model showed that hypertension negatively affected HRQoL in the study population (estimate = −1.85, p < 0.0001). According to the STEPP analysis, we found that the EQ-VAS score in the hypertension group was lower than that in non-hypertension group for every age group. Additionally, the results of subgroup analyses indicated that the difference of score between two groups was larger among young women. When compared to respondents without hypertension, respondents with hypertension experienced lower HRQoL regardless of gender or any range of age. Furthermore, the impact of hypertension on HRQoL of young women might be more obvious.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Milner J, Wilkinson P. Trends in cause-specific mortality in Chinese provinces. Lancet. 2016;387:204–5.
Ruan Y, Mo M, Joss-Moore L, Li YY, Yang QD, Shi L, et al. Increased waist circumference and prevalence of type 2 diabetes and hypertension in Chinese adults: two population-based cross-sectional surveys in Shanghai, China. BMJ Open. 2013;3:e003408.
Zhou M, Wang H, Zhu J, Chen W, Wang L, Liu, et al. Cause-specific mortality for 240 causes in China during 1990–2013: a systematic subnational analysis for the global burden of disease study 2013. Lancet. 2016;387:251–72.
Wu Y, Huxley R, Li L, Anna V, Xie G, Yao C, et al. Prevalence, awareness, treatment, and control of hypertension in China: data from the China national nutrition and health survey 2002. Circulation. 2008;118:2679–86.
Cohen AJ, Brauer M, Burnett R, Anderson HR, Frostad J, Estep, et al. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the global burden of diseases study 2015. Lancet. 2017;389:1907–18.
Zahran HS, Kobau R, Moriarty DG, Zack MM, Holt J, Donehoo R, et al. Health-related quality of life surveillance—United States, 1993–2002. Morb Mortal Wkly Rep Surveill Summ. 2005;54:1–35.
Brazier JE, Yang Y, Tsuchiya A, Rowen DL. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ: HEPAC: Health Econ Prev care. 2010;11:215–25.
EuroQol G. EuroQol—a new facility for the measurement of health-related quality of life. Health Policy. 1990;16:199–208.
Lu Y, Wang N, Chen Y, Nie X, Li Q, Han B, et al. Health-related quality of life in type-2 diabetes patients: a cross-sectional study in East China. BMC Endocr Disord. 2017;17:38.
Taype-Rondan A, Abbs ES, Lazo-Porras M, Checkley W, Gilman RH, Smeeth L, et al. Association between chronic conditions and health-related quality of life: differences by level of urbanization in Peru. Qual Life Res: Int J Qual life Asp Treat Care Rehabil. 2017;26:3439–47.
Nolan CM, Longworth L, Lord J, Canavan JL, Jones SE, Kon SS, et al. The EQ-5D-5L health status questionnaire in COPD: validity, responsiveness and minimum important difference. Thorax. 2016;71:493–500.
Zhang L, Guo X, Zhang J, Chen X, Zhou C, Ge D, et al. Health-related quality of life among adults with and without hypertension: a population-based survey using EQ-5D in Shandong, China. Sci Rep. 2017;7:14960.
Zhang Y, Zhou Z, Gao J, Wang D, Zhang Q, Zhou Z, et al. Health-related quality of life and its influencing factors for patients with hypertension: evidence from the urban and rural areas of Shaanxi Province, China. BMC Health Serv Res. 2016;16:277.
Wang R, Zhao Y, He X, Ma X, Yan X, Sun Y, et al. Impact of hypertension on health-related quality of life in a population-based study in Shanghai, China. Public Health. 2009;123:534–9.
Xu Y, Gao J, Zhou Z, Xue Q, Yang J, Luo H, et al. Measurement and explanation of socioeconomic inequality in catastrophic health care expenditure: evidence from the rural areas of Shaanxi Province. BMC Health Serv Res. 2015;15:256.
Yuefeng L, Keqin R, Xiaowei R. Use of and factors associated with self-treatment in China. BMC Public Health. 2012;12:995.
EQ-5D-3L User Guide: Basic information on how to use the EQ-5D-3L instrument. Version 5.1. April 2015. https://euroqol.org/publications/user-guides/.
Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res: Int J Qual life Asp Treat Care Rehabil. 2013;22:1717–27.
Liu GG, Wu H, Li M, Gao C, Luo N. Chinese time trade-off values for EQ-5D health states. Value Health: J Int Soc Pharm Outcomes Res. 2014;17:597–604.
Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i–xii. 1–253
Bonetti M, Gelber RD. A graphical method to assess treatment–covariate interactions using the Cox model on subsets of the data. Stat Med. 2000;19:2595–609.
Bonetti M, Gelber RD. Patterns of treatment effects in subsets of patients in clinical trials. Biostatistics. 2004;5:465–81.
Yip WK, Bonetti M, Cole BF, Barcella W, Wang XV, Lazar A, et al. Subpopulation treatment effect pattern plot (STEPP) analysis for continuous, binary, and count outcomes. Clin Trials. 2016;13:382–90.
Pan W. Akaike’s information criterion in generalized estimating equations. Biometrics. 2001;57:120–5.
Meng Q, Xu L, Zhang Y, Qian J, Cai M, Xin, et al. Trends in access to health services and financial protection in China between 2003 and 2011: a cross-sectional study. Lancet. 2012;379:805–14.
Fu D, Fu H, McGowan P, Shen YE, Zhu L, Yang H, et al. Implementation and quantitative evaluation of chronic disease self-management programme in Shanghai, China: randomized controlled trial. Bull World Health Organ. 2003;81:174–82.
Chin YR, Lee IS, Lee HY. Effects of hypertension, diabetes, and/or cardiovascular disease on health-related quality of life in elderly Korean individuals: a population-based cross-sectional survey. Asian Nurs Res. 2014;8:267–73.
Sullivan PW, Ghushchyan VH, Ben-Joseph R. The impact of obesity on diabetes, hyperlipidemia and hypertension in the United States. Qual Life Res: Int J Qual life Asp Treat Care Rehabil. 2008;17:1063–71.
Yayan J. Association of traditional risk factors with coronary artery disease in nonagenarians: the primary role of hypertension. Clin Interv Aging. 2014;9:2003–12.
Bardage C, Isacson DG. Hypertension and health-related quality of life. An epidemiological study in Sweden. J Clin Epidemiol. 2001;54:172–81.
Ning M, Zhang Q, Yang M. Comparison of self-reported and biomedical data on hypertension and diabetes: findings from the China Health and Retirement Longitudinal Study (CHARLS). BMJ Open. 2016;6:e009836.
Acknowledgements
We appreciate the Shanghai Municipal Commission Health and Family Planning for their assistance in designing this study. We also thank the participates and data managers who gave their time and effort to participate in the fifth Health Service Survey of Shanghai.
Funding
This study was conducted under a grant from the Fourth Round of Shanghai Three-year Action Plan on Public Health Discipline and Talent Program: Evidence-based Public Health and Health Economics (No. 15GWZK0901), and was also sponsored by Shanghai Sailing Program (No. 18YF1429500) and the National Nature Science Foundation of China (No. 81502880).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Electronic supplementary material
Rights and permissions
About this article
Cite this article
Qin, Y., Guo, Y., Tang, Y. et al. Impact of hypertension on health-related quality of life among different age subgroups in Shanghai: the subpopulation treatment effect pattern plot analysis. J Hum Hypertens 33, 78–86 (2019). https://doi.org/10.1038/s41371-018-0092-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41371-018-0092-8
This article is cited by
-
Applying SF-6D to measure health state utilities among the middle and old aged patients with hypertension in China
Health and Quality of Life Outcomes (2020)