IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i18p3471-d268302.html
   My bibliography  Save this article

Does Social Support Affect the Health of the Elderly in Rural China? A Meta-Analysis Approach

Author

Listed:
  • Natuya Zhuori

    (College of Economics and Management, Northwest Agriculture and Forestry University, Yangling 712100, China)

  • Yu Cai

    (College of Economics and Management, Northwest Agriculture and Forestry University, Yangling 712100, China)

  • Yan Yan

    (College of Economics and Management, Northwest Agriculture and Forestry University, Yangling 712100, China)

  • Yu Cui

    (College of Economics and Management, Northwest Agriculture and Forestry University, Yangling 712100, China)

  • Minjuan Zhao

    (College of Economics and Management, Northwest Agriculture and Forestry University, Yangling 712100, China)

Abstract

As the trend of aging in rural China has intensified, research on the factors affecting the health of the elderly in rural areas has become a hot issue. However, the conclusions of existing studies are inconsistent and even contradictory, making it difficult to form constructive policies with practical value. To explore the reasons for the inconsistent conclusions drawn by relevant research, in this paper we constructed a meta-regression database based on 65 pieces of relevant literature published in the past 25 years. For more valid samples to reduce publication bias, we also set the statistical significance of social support to the health of the elderly in rural areas as a dependent variable. Finally, combined with multi-dimensional social support and its implications for the health of the elderly, meta-regression analysis was carried out on the results of 171 empirical studies. The results show that (1) subjective support rather than objective support can have a significant impact on the health of the elderly in rural areas, and there is no significant difference between other dimensions of social support and objective support; (2) the health status of the elderly in rural areas in samples involving western regions is more sensitive to social support than that in samples not involving the western regions; (3) among the elderly in rural areas, social support for the older male elderly is more likely to improve their health than that for the younger female elderly; and (4) besides this, both data sources and econometric models greatly affect the heterogeneity of the effect of social support on the health of the elderly in rural areas, but neither the published year nor the journal is significant. Finally, relevant policies and follow-up studies on the impact of social support on the health of the elderly in rural areas are discussed.

Suggested Citation

  • Natuya Zhuori & Yu Cai & Yan Yan & Yu Cui & Minjuan Zhao, 2019. "Does Social Support Affect the Health of the Elderly in Rural China? A Meta-Analysis Approach," IJERPH, MDPI, vol. 16(18), pages 1-15, September.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:18:p:3471-:d:268302
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/18/3471/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/16/18/3471/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. T.D. Stanley & Hristos Doucouliagos & Margaret Giles & Jost H. Heckemeyer & Robert J. Johnston & Patrice Laroche & Jon P. Nelson & Martin Paldam & Jacques Poot & Geoff Pugh & Randall S. Rosenberger & , 2013. "Meta-Analysis Of Economics Research Reporting Guidelines," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 390-394, April.
    2. T. D. Stanley & Stephen B. Jarrell, 2005. "Meta‐Regression Analysis: A Quantitative Method of Literature Surveys," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 299-308, July.
    3. A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, March.
    4. T.D. Stanley & Hristos Doucouliagos & Margaret Giles & Jost Heckemeyer & Robert Johnston & Patrice Laroche & Jon Nelson & Martin Paldam & Jacques Poot & Geoff Pugh & Randall Rosenberger & Katja Rost, 2013. "Meta-analysis of economics research reporting guidelines," Post-Print hal-02137661, HAL.
    5. Edward Oczkowski & Hristos Doucouliagos, 2015. "Wine Prices and Quality Ratings: A Meta-regression Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 103-121.
    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. Hsuan-Hui Chen & Pei-Lin Hsieh, 2021. "Applying the Pender’s Health Promotion Model to Identify the Factors Related to Older Adults’ Participation in Community-Based Health Promotion Activities," IJERPH, MDPI, vol. 18(19), pages 1-17, September.
    2. Rachelle Meisters & Polina Putrik & Daan Westra & Hans Bosma & Dirk Ruwaard & Maria Jansen, 2021. "Is Loneliness an Undervalued Pathway between Socio-Economic Disadvantage and Health?," IJERPH, MDPI, vol. 18(19), pages 1-13, September.

    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. Stanley, T. D. & Doucouliagos, Chris, 2019. "Practical Significance, Meta-Analysis and the Credibility of Economics," IZA Discussion Papers 12458, Institute of Labor Economics (IZA).
    2. Klomp, Jeroen, 2023. "Political budget cycles in military expenditures: A meta-analysis," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 1083-1102.
    3. Nicolas Fleury & Fabrice Gilles, 2015. "A meta-regression analysis on intergenerational transmission of education: publication bias and genuine empirical effect," TEPP Working Paper 2015-02, TEPP.
    4. Heinemann, Friedrich & Moessinger, Marc-Daniel & Yeter, Mustafa, 2018. "Do fiscal rules constrain fiscal policy? A meta-regression-analysis," European Journal of Political Economy, Elsevier, vol. 51(C), pages 69-92.
    5. Ugur, Mehmet & Trushin, Eshref & Solomon, Edna & Guidi, Francesco, 2016. "R&D and productivity in OECD firms and industries: A hierarchical meta-regression analysis," Research Policy, Elsevier, vol. 45(10), pages 2069-2086.
    6. Beltrán, Allan & Alatorre, José Eduardo & Ferrer, Jimy & Galindo, Luis Miguel, 2017. "Efectos potenciales de un impuesto al carbono sobre el producto interno bruto en los países de América Latina: estimaciones preliminares e hipotéticas a partir de un metaanálisis y una función de tran," Documentos de Proyectos 41867, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    7. Petr Polák, 2019. "The Euro'S Trade Effect: A Meta‐Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 33(1), pages 101-124, February.
    8. Lan Nguyen, Thi Mai & Papyrakis, Elissaios & van Bergeijk, Peter A.G., 2021. "Publication bias in the price effects of monetary policy: A meta-regression analysis for emerging and developing economies," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 567-583.
    9. Chaikumbung, Mayula & Doucouliagos, Hristos & Scarborough, Helen, 2016. "The economic value of wetlands in developing countries: A meta-regression analysis," Ecological Economics, Elsevier, vol. 124(C), pages 164-174.
    10. Branger, Frédéric & Quirion, Philippe, 2014. "Would border carbon adjustments prevent carbon leakage and heavy industry competitiveness losses? Insights from a meta-analysis of recent economic studies," Ecological Economics, Elsevier, vol. 99(C), pages 29-39.
    11. Markus Hang & Jerome Geyer‐Klingeberg & Andreas Rathgeber & Stefan Stöckl, 2018. "Economic Development Matters: A Meta‐Regression Analysis on the Relation between Environmental Management and Financial Performance," Journal of Industrial Ecology, Yale University, vol. 22(4), pages 720-744, August.
    12. Liang-Cheng Zhang & Andrew C. Worthington, 2018. "Explaining Estimated Economies of Scale and Scope in Higher Education: A Meta-Regression Analysis," Research in Higher Education, Springer;Association for Institutional Research, vol. 59(2), pages 156-173, March.
    13. Germà Bel & Mildred E. Warner, 2016. "Factors explaining inter-municipal cooperation in service delivery: a meta-regression analysis," Journal of Economic Policy Reform, Taylor and Francis Journals, vol. 19(2), pages 91-115, April.
    14. de Freitas, Carlos Eduardo & Paes, Nelson Leitão, 2019. "The collapse of Brazilian Social Security: Macroeconomic impacts of the increase of the minimum age of PEC nº 287/2016 reform," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 39(1), July.
    15. Cerdá, Emilio & López-Otero, Xiral & Quiroga, Sonia & Soliño, Mario, 2024. "Willingness to pay for renewables: Insights from a meta-analysis of choice experiments," Energy Economics, Elsevier, vol. 130(C).
    16. Demena, Binyam Afewerk & Afesorgbor, Sylvanus Kwaku, 2020. "The effect of FDI on environmental emissions: Evidence from a meta-analysis," Energy Policy, Elsevier, vol. 138(C).
    17. Iamsiraroj, Sasi & Doucouliagos, Hristos, 2015. "Does growth attract FDI?," Economics Discussion Papers 2015-18, Kiel Institute for the World Economy (IfW Kiel).
    18. Bruno, Randolph Luca & Campos, Nauro F. & Estrin, Saul, 2018. "Taking stock of firm-level and country-level benefits from foreign direct investment," LSE Research Online Documents on Economics 87343, London School of Economics and Political Science, LSE Library.
    19. Peter H. Howard & Thomas Sterner, 2017. "Few and Not So Far Between: A Meta-analysis of Climate Damage Estimates," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(1), pages 197-225, September.
    20. Jiří Gregor & Aleš Melecký & Martin Melecký, 2021. "Interest Rate Pass‐Through: A Meta‐Analysis Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 141-191, February.

    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:16:y:2019:i:18:p:3471-:d:268302. 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.