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Estimating Transition Probabilities for Modeling Major Depression in Adolescents by Sex and Race or Ethnicity Combinations in the USA

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Abstract

Objective

About one-fifth of US adolescents experienced major depressive symptoms, but few studies have examined longitudinal trends of adolescents developing depression or recovering by demographic factors. We estimated new transition probability inputs, and then used them in a simulation model to project the epidemiologic burden and trajectory of depression of diverse adolescents by sex and race or ethnicity combinations.

Methods

Transition probabilities were first derived using parametric survival analysis of data from the National Longitudinal Study of Adolescent to Adult Health and then calibrated to cross-sectional data from the National Survey on Drug Use and Health. We developed a cohort state-transition model to simulate age-specific depression outcomes of US adolescents. A hypothetical adolescent cohort was modeled from 12−22 years with annual transitions. Model outcomes included proportions of youth experiencing depression, recovery, or depression-free cases and were reported for a US adolescent population by sex, race or ethnicity, and sex and race or ethnicity combinations.

Results

At 22 years of age, approximately 16% of adolescents had depression, 12% were in recovery, and 72% had never developed depression. Depression prevalence peaked around 16–17 years-old. Adolescents of multiracial or other race or ethnicity, White, American Indian or Alaska Native, and Hispanic, Latino, or Spanish descent were more likely to experience depression than other racial or ethnic groups. Depression trajectories generated by the model matched well with historical observational studies by sex and race or ethnicity, except for individuals from American Indian or Alaska Native and multiracial or other race or ethnicity backgrounds.

Conclusions

This study validated new transition probabilities for future use in decision models evaluating adolescent depression policies or interventions. Different sets of transition parameters by demographic factors (sex and race or ethnicity combinations) were generated to support future health equity research, including distributional cost-effectiveness analysis. Further data disaggregated with respect to race, ethnicity, religion, income, geography, gender identity, sexual orientation, and disability would be helpful to project accurate estimates for historically minoritized communities.

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Acknowledgements

This work was supported by the Health Policy Research Scholars program by the Robert Wood Johnson Foundation as well as the Rackham Merit Fellowship and Avedis Donabedian Award based at the University of Michigan. We appreciatively acknowledged the team Decision Analysis in R for Technologies in Health, particularly Drs. Eline M. Krijkamp and Petros Pechlivanoglou for their contribution to the development of the code for survival analysis. We also gratefully acknowledged Woosub Shin and Xiru Lyu for their help with general coding in R software.

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Authors and Affiliations

  1. Department of Pediatrics, University of Pittsburgh School of Medicine, 3414 Fifth Avenue, 1st Floor, Pittsburgh, PA, 15213-3205, USA

    Tran T. Doan

  2. Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor, MI, USA

    David W. Hutton & Lisa A. Prosser

  3. Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA, USA

    Davene R. Wright

  4. Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, USA

    Lisa A. Prosser

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  1. Tran T. Doan
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Corresponding author

Correspondence to Tran T. Doan.

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Funding

This research was funded by the Health Policy Research Scholars program by the Robert Wood Johnson Foundation as well as the Rackham Merit Fellowship and Avedis Donabedian Fellowship based at the University of Michigan.

Conflict of Interest

The authors declare no competing interests.

Ethics Approval and Consent to Participate

Seeking approval or consent to participate was not required by the University of Michigan's Institutional Review Board because this study did not perform research on human participants.

Data Availability

Secondary datasets from the National Longitudinal Study of Adolescent to Adult Health as well as the National Survey on Drug Use and Health are publicly available online.

Code Availability

Data files and other materials used and/or analyzed during this study are available upon request from the corresponding author.

Author Contributions

Conception and design of the work—T.D., L.P., D.H., D.W.; acquisition and analysis of the data—T.D.; interpretation of the data—T.D., L.P., D.H., D.W.; drafting the work— T.D.; revising draft for important intellectual content—T.D., L.P., D.H., D.W.; final approvals for publication and agreement to be accountable for all aspects of the work— T.D., L.P., D.H., D.W.

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Doan, T.T., Hutton, D.W., Wright, D.R. et al. Estimating Transition Probabilities for Modeling Major Depression in Adolescents by Sex and Race or Ethnicity Combinations in the USA. Appl Health Econ Health Policy 22, 375–390 (2024). https://doi.org/10.1007/s40258-024-00872-6

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