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Time Preferences Predict Mortality among HIV-Infected Adults Receiving Antiretroviral Therapy in Kenya

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  • Harsha Thirumurthy
  • Kami Hayashi
  • Sebastian Linnemayr
  • Rachel C Vreeman
  • Irwin P Levin
  • David R Bangsberg
  • Noel T Brewer

Abstract

Background: Identifying characteristics of HIV-infected adults likely to have poor treatment outcomes can be useful for targeting interventions efficiently. Research in economics and psychology suggests that individuals’ intertemporal time preferences, which indicate the extent to which they trade-off immediate vs. future cost and benefits, can influence various health behaviors. While there is empirical support for the association between time preferences and various non-HIV health behaviors and outcomes, the extent to which time preferences predict outcomes of those receiving antiretroviral therapy (ART) has not been examined previously. Methods: HIV-infected adults initiating ART were enrolled at a health facility in Kenya. Participants’ time preferences were measured at enrollment and used to classify them as having either a low or high discount rate for future benefits. At 48 weeks, we assessed mortality and ART adherence, as measured by Medication Event Monitoring System (MEMS). Logistic regression models adjusting for socio-economic characteristics and risk factors were used to determine the association between time preferences and mortality as well as MEMS adherence ≥90%. Results: Overall, 44% (96/220) of participants were classified as having high discount rates. Participants with high discount rates had significantly higher 48-week mortality than participants with low discount rates (9.3% vs. 3.1%; adjusted odds ratio 3.84; 95% CI 1.03, 14.50). MEMS adherence ≥90% was similar for participants with high vs. low discount rates (42.3% vs. 49.6%, AOR 0.70; 95% CI 0.40, 1.25). Conclusion: High discount rates were associated with significantly higher risk of mortality among HIV-infected patients initiating ART. Greater use of time preference measures may improve identification of patients at risk of poor clinical outcomes. More research is needed to further identify mechanisms of action and also to build upon and test the generalizability of this finding.

Suggested Citation

  • Harsha Thirumurthy & Kami Hayashi & Sebastian Linnemayr & Rachel C Vreeman & Irwin P Levin & David R Bangsberg & Noel T Brewer, 2015. "Time Preferences Predict Mortality among HIV-Infected Adults Receiving Antiretroviral Therapy in Kenya," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-8, December.
    • Handle: RePEc:plo:pone00:0145245
    DOI: 10.1371/journal.pone.0145245
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    References listed on IDEAS

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    1. Smith, Patricia K. & Bogin, Barry & Bishai, David, 2005. "Are time preference and body mass index associated?: Evidence from the National Longitudinal Survey of Youth," Economics & Human Biology, Elsevier, vol. 3(2), pages 259-270, July.
    2. Shane Frederick & George Loewenstein & Ted O'Donoghue, 2002. "Time Discounting and Time Preference: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 40(2), pages 351-401, June.
    3. Dorte Gyrd-Hansen, 2002. "Comparing the results of applying different methods of eliciting time preferences for health," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 3(1), pages 10-16, March.
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    1. Norrgren, Lisa, 2022. "Time preference, illness, and death," Journal of Health Economics, Elsevier, vol. 86(C).
    2. Norrgren, Lisa, 2021. "Time Preferences, Illness, and Death," Working Papers in Economics 812, University of Gothenburg, Department of Economics, revised 11 Oct 2021.

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