IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i19p10009-d641392.html
   My bibliography  Save this article

Economic Burden of Depressive Symptoms Conditions among Middle-Aged and Elderly People with Hypertension in China

Author

Listed:
  • Yun Wu

    (Department of Health Policy and Management, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China
    Authors contribute equally to this article.)

  • Dongbao Zhao

    (Department of Health Policy and Management, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China
    Authors contribute equally to this article.)

  • Jianwei Guo

    (Department of Health Policy and Management, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China)

  • Yingsi Lai

    (Department of Health Medical Statistics, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China)

  • Lijin Chen

    (Department of Health Policy and Management, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China)

  • Sihui Jin

    (Department of Health Policy and Management, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China)

  • Yixiang Huang

    (Department of Health Policy and Management, School of Public Health, Sun Yat-sen University, 74, Zhongshan 2nd Road, Guangzhou 510030, China)

Abstract

People with hypertension are more prone to incur depressive symptoms, while depressive symptoms have an obvious influence on the healthy functioning, treatment, and management of hypertensive patients. However, there have been limited studies on the association between depression and the economic burden of hypertension. We used data from the 2018 China Health and Retirement Longitudinal Study (CHARLS) to estimate the additional annual direct and indirect economic burden of depressive symptoms among middle-aged and elderly hypertensive patients with a multivariable regression model. The depressive symptoms were associated with substantial additional direct and indirect economic burden. Compared with non-co-MHDS (non-co-morbid hypertension and depressive symptoms) patients, the direct economic burden of lower co-MHDS (co-morbid hypertension and depressive symptoms) patients and higher co-MHDS patients increased 1887.4 CNY and 5508.4 CNY, respectively. For indirect economic burden, the lower co-MHDS patients increased 331.2 CNY and the higher co-MHDS patients increased 636.8 CNY. Both direct and indirect economic burden were incremental with the aggravation of depressive symptoms. The results showed depressive symptoms increased total healthcare costs by increasing the utilization and expenditure of primary healthcare services. Depressive symptoms also led to economic loss of productivity, especially for agricultural workers. This study highlights the importance of mental healthcare for hypertensive patients.

Suggested Citation

  • Yun Wu & Dongbao Zhao & Jianwei Guo & Yingsi Lai & Lijin Chen & Sihui Jin & Yixiang Huang, 2021. "Economic Burden of Depressive Symptoms Conditions among Middle-Aged and Elderly People with Hypertension in China," IJERPH, MDPI, vol. 18(19), pages 1-11, September.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:19:p:10009-:d:641392
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/19/10009/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/19/10009/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chee‐Ruey Hsieh & Xuezheng Qin, 2018. "Depression hurts, depression costs: The medical spending attributable to depression and depressive symptoms in China," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 525-544, March.
    2. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
    3. Jinqi Jiang & Wanzhen Huang & Zhenhua Wang & Guangsheng Zhang, 2019. "The Effect of Health on Labour Supply of Rural Elderly People in China—An Empirical Analysis Using CHARLS Data," IJERPH, MDPI, vol. 16(7), pages 1-15, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gun-Young Lee & Kyung-O Kim & Jae-Hyeong Ryu & Sun-Hee Park & Hae-Ryong Chung & Marcia Butler, 2022. "Exploring Perceived Barriers to Physical Activity in Korean Older Patients with Hypertension: Photovoice Inquiry," IJERPH, MDPI, vol. 19(21), pages 1-22, October.
    2. Yun Wu & Sihui Jin & Jianwei Guo & Yi Zhu & Lijin Chen & Yixiang Huang, 2022. "The Economic Burden Associated with Depressive Symptoms among Middle-Aged and Elderly People with Chronic Diseases in China," IJERPH, MDPI, vol. 19(19), pages 1-14, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Noemi Kreif & Richard Grieve & Rosalba Radice & Zia Sadique & Roland Ramsahai & Jasjeet S. Sekhon, 2012. "Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data," Medical Decision Making, , vol. 32(6), pages 750-763, November.
    2. Wendy Hens & Dirk Vissers & Nick Verhaeghe & Jan Gielen & Luc Van Gaal & Jan Taeymans, 2021. "Unsupervised Exercise Training Was Not Found to Improve the Metabolic Health or Phenotype over a 6-Month Dietary Intervention: A Randomised Controlled Trial with an Embedded Economic Analysis," IJERPH, MDPI, vol. 18(15), pages 1-13, July.
    3. Jun Zhang & Yuang He & Jing Zhang, 2022. "Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach," IJERPH, MDPI, vol. 19(2), pages 1-21, January.
    4. Zhong, Jingdong & Wang, Tianyi & He, Yang & Gao, Jingjing & Liu, Chengfang & Lai, Fang & Zhang, Liuxiu & Luo, Renfu, 2021. "Interrelationships of caregiver mental health, parenting practices, and child development in rural China," Children and Youth Services Review, Elsevier, vol. 121(C).
    5. Jun-Hui Wu & Yao Wu & Zi-Jing Wang & Yi-Qun Wu & Tao Wu & Meng-Ying Wang & Xiao-Wen Wang & Si-Yue Wang & Jia-Ting Wang & Huan Yu & Yong-Hua Hu, 2021. "Healthcare Costs Associated with Complications in Patients with Type 2 Diabetes among 1.85 Million Adults in Beijing, China," IJERPH, MDPI, vol. 18(7), pages 1-10, April.
    6. Zhiyuan Hou & Ellen Van de Poel & Eddy Van Doorslaer & Baorong Yu & Qingyue Meng, 2014. "Effects Of Ncms On Access To Care And Financial Protection In China," Health Economics, John Wiley & Sons, Ltd., vol. 23(8), pages 917-934, August.
    7. Caballer-Tarazona, Vicent & Guadalajara-Olmeda, Natividad & Vivas-Consuelo, David, 2019. "Predicting healthcare expenditure by multimorbidity groups," Health Policy, Elsevier, vol. 123(4), pages 427-434.
    8. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2012. "The Influence of BMI, Obesity and Overweight on Medical Costs: A Panel Data Approach," Working Papers 2012-08, FEDEA.
    9. Tor Iversen & Eline Aas & Gunnar Rosenqvist & Unto Häkkinen & on behalf of the EuroHOPE study group, 2015. "Comparative Analysis of Treatment Costs in EUROHOPE," Health Economics, John Wiley & Sons, Ltd., vol. 24(S2), pages 5-22, December.
    10. Jay Dev Dubey, 2021. "Measuring Income Elasticity of Healthcare-Seeking Behavior in India: A Conditional Quantile Regression Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 767-793, December.
    11. Chen, Yanran & Sun, Ruochen & Chen, Xi & Qin, Xuezheng, 2023. "Does extreme temperature exposure take a toll on mental health? Evidence from the China Health and Retirement Longitudinal Study," Environment and Development Economics, Cambridge University Press, vol. 28(5), pages 486-510, October.
    12. Kaushik Ghosh & Irina Bondarenko & Kassandra L Messer & Susan T Stewart & Trivellore Raghunathan & Allison B Rosen & David M Cutler, 2020. "Attributing medical spending to conditions: A comparison of methods," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.
    13. Fan Yang & Brenda Gannon & Andrew Weightman, 2018. "Public’s Willingness to Pay Towards a Medical Device for Detecting Foot Ulceration in People with Diabetes," Applied Health Economics and Health Policy, Springer, vol. 16(4), pages 559-567, August.
    14. Kurt Lavetti & Thomas DeLeire & Nicolas R. Ziebarth, 2023. "How do low‐income enrollees in the Affordable Care Act marketplaces respond to cost‐sharing?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(1), pages 155-183, March.
    15. Angioloni, Simone & Sherry, Erin & Wu, Ziping, 2017. "Evaluating the Effectiveness of Axis 3-LEADER Grants on Job Creation," 91st Annual Conference, April 24-26, 2017, Royal Dublin Society, Dublin, Ireland 258643, Agricultural Economics Society.
    16. Wameq A. Raza & Ellen van de Poel & Arjun Bedi & Frans Rutten, 2016. "Impact of Community‐based Health Insurance on Access and Financial Protection: Evidence from Three Randomized Control Trials in Rural India," Health Economics, John Wiley & Sons, Ltd., vol. 25(6), pages 675-687, June.
    17. Galina Besstremyannaya, 2012. "Estimating income equity in social health insurance system," Working Papers w0172, New Economic School (NES).
    18. Yun Wu & Sihui Jin & Jianwei Guo & Yi Zhu & Lijin Chen & Yixiang Huang, 2022. "The Economic Burden Associated with Depressive Symptoms among Middle-Aged and Elderly People with Chronic Diseases in China," IJERPH, MDPI, vol. 19(19), pages 1-14, October.
    19. Wang, Tianyu & Sun, Ruochen & Sindelar, Jody L. & Chen, Xi, 2024. "Occupational differences in the effects of retirement on hospitalizations for mental illness among female workers: Evidence from administrative data in China," Economics & Human Biology, Elsevier, vol. 53(C).
    20. Nie, Peng & Li, Qiaoge & Sousa-Poza, Alfonso, 2021. "Energy poverty and subjective well-being in China: New evidence from the China Family Panel Studies," Energy Economics, Elsevier, vol. 103(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:19:p:10009-:d:641392. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.