Identifying covariates of population health using extreme bound analysis.

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  • Author(s): Carmignani F;Carmignani F; Shankar S; Tan EJ; Tang KK
  • Source:
    The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care [Eur J Health Econ] 2014 Jun; Vol. 15 (5), pp. 515-31. Date of Electronic Publication: 2013 Jun 14.
  • Publication Type:
    Journal Article; Research Support, Non-U.S. Gov't
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101134867 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1618-7601 (Electronic) Linking ISSN: 16187598 NLM ISO Abbreviation: Eur J Health Econ Subsets: MEDLINE
    • Publication Information:
      Original Publication: Berlin : Springer-Verlag, c2001-
    • Subject Terms:
    • Abstract:
      Background: The literature is full of lively discussion on the determinants of population health outcomes. However, different papers focus on small and different sets of variables according to their research agenda. Because many of these variables are measures of different aspects of development and are thus correlated, the results for one variable can be sensitive to the inclusion/exclusion of others.
      Method: We tested for the robustness of potential predictors of population health using the extreme bounds analysis. Population health was measured by life expectancy at birth and infant mortality rate.
      Results: We found that only about half a dozen variables are robust predictors for life expectancy and infant mortality rate. Among them, adolescent fertility rate, improved water sources, and gender equality are the most robust. All institutional variables and environment variables are systematically non-robust predictors of population health.
      Conclusion: The results highlight the importance of robustness tests in identifying predictors or potential determinants of population health, and cast doubts on the findings of previous studies that fail to do so.
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    • Publication Date:
      Date Created: 20130615 Date Completed: 20150126 Latest Revision: 20181113
    • Publication Date:
      20181211
    • Accession Number:
      10.1007/s10198-013-0492-1
    • Accession Number:
      23765332
  • Citations
    • ABNT:
      CARMIGNANI, F. et al. Identifying covariates of population health using extreme bound analysis. The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care, [s. l.], v. 15, n. 5, p. 515–531, 2014. DOI 10.1007/s10198-013-0492-1. Disponível em: http://widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdc&AN=23765332&authtype=sso&custid=s5834912. Acesso em: 27 jan. 2020.
    • AMA:
      Carmignani F, Shankar S, Tan EJ, Tang KK. Identifying covariates of population health using extreme bound analysis. The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care. 2014;15(5):515-531. doi:10.1007/s10198-013-0492-1.
    • APA:
      Carmignani, F., Shankar, S., Tan, E. J., & Tang, K. K. (2014). Identifying covariates of population health using extreme bound analysis. The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care, 15(5), 515–531. https://doi.org/10.1007/s10198-013-0492-1
    • Chicago/Turabian: Author-Date:
      Carmignani, Fabrizio, Sriram Shankar, Eng Joo Tan, and Kam Ki Tang. 2014. “Identifying Covariates of Population Health Using Extreme Bound Analysis.” The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care 15 (5): 515–31. doi:10.1007/s10198-013-0492-1.
    • Harvard:
      Carmignani, F. et al. (2014) ‘Identifying covariates of population health using extreme bound analysis’, The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care, 15(5), pp. 515–531. doi: 10.1007/s10198-013-0492-1.
    • Harvard: Australian:
      Carmignani, F, Shankar, S, Tan, EJ & Tang, KK 2014, ‘Identifying covariates of population health using extreme bound analysis’, The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care, vol. 15, no. 5, pp. 515–531, viewed 27 January 2020, .
    • MLA:
      Carmignani, Fabrizio, et al. “Identifying Covariates of Population Health Using Extreme Bound Analysis.” The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care, vol. 15, no. 5, June 2014, pp. 515–531. EBSCOhost, doi:10.1007/s10198-013-0492-1.
    • Chicago/Turabian: Humanities:
      Carmignani, Fabrizio, Sriram Shankar, Eng Joo Tan, and Kam Ki Tang. “Identifying Covariates of Population Health Using Extreme Bound Analysis.” The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care 15, no. 5 (June 2014): 515–31. doi:10.1007/s10198-013-0492-1.
    • Vancouver/ICMJE:
      Carmignani F, Shankar S, Tan EJ, Tang KK. Identifying covariates of population health using extreme bound analysis. The European Journal Of Health Economics: HEPAC: Health Economics In Prevention And Care [Internet]. 2014 Jun [cited 2020 Jan 27];15(5):515–31. Available from: http://widgets.ebscohost.com/prod/customlink/proxify/proxify.php?count=1&encode=0&proxy=&find_1=&replace_1=&target=http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdc&AN=23765332&authtype=sso&custid=s5834912