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Taking the Measure of a Fatal Drug Epidemic

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  • Christopher J. Ruhm

Abstract

This analysis utilizes death certificate data from the Multiple Cause of Death (MCOD) files to better measure the specific drugs involved in drug poisoning fatalities. Statistical adjustment procedures are used to provide more accurate estimates, accounting for the understatement in death certificate reports resulting because no drug is specified in between one-fifth and one-quarter of cases. The adjustment procedures typically raise the estimates of specific types of drug involvement by 30% to 50% and emphasize the importance of the simultaneous use of multiple categories of drugs. Using these adjusted estimates, an analysis is next provided of drugs accounting for the rapid increase over time in fatal overdoses. The frequency of combination drug use introduces uncertainty into these estimates and so a distinction is made between any versus exclusive involvement of specific drug types. Many of the results are sensitive to the starting and ending years chosen for examination, with a key role of prescription opioids for analysis windows starting in 1999 but with other drugs, particularly heroin deaths, becoming more significant in more recent years and, again, with confirmatory evidence of the importance of simultaneous drug use.

Suggested Citation

  • Christopher J. Ruhm, 2016. "Taking the Measure of a Fatal Drug Epidemic," NBER Working Papers 22504, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:22504
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    1. Rockett, I.R.H. & Smith, G.S. & Caine, E.D. & Kapusta, N.D. & Hanzlick, R.L. & Larkin, G.L. & Naylor, C.P.E. & Nolte, K.B. & Miller, T.R. & Putnam, S.L. & De Leo, D. & Kleinig, J. & Stack, S. & Todd, , 2014. "Confronting death from drug self-intoxication (DDSI): Prevention through a better definition," American Journal of Public Health, American Public Health Association, vol. 104(12), pages 49-55.
    2. Ruhm, Christopher J., 2015. "Recessions, healthy no more?," Journal of Health Economics, Elsevier, vol. 42(C), pages 17-28.
    3. Ellen Meara, 2001. "Why is Health Related to Socioeconomic Status?," NBER Working Papers 8231, National Bureau of Economic Research, Inc.
    4. Carpenter, Christopher S. & McClellan, Chandler B. & Rees, Daniel I., 2017. "Economic conditions, illicit drug use, and substance use disorders in the United States," Journal of Health Economics, Elsevier, vol. 52(C), pages 63-73.
    5. Anne Case & Angua Deaton, 2015. "Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century," Working Papers 15078.full.pdf, Princeton University, Woodrow Wilson School of Public and International Affairs, Research Program in Development Studies..
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    Cited by:

    1. Simone Balestra & Helge Liebert & Nicole Maestas & Tisamarie B. Sherry, 2021. "Behavioral Responses to Supply-Side Drug Policy During the Opioid Epidemic," NBER Working Papers 29596, National Bureau of Economic Research, Inc.
    2. Aliprantis, Dionissi & Fee, Kyle & Schweitzer, Mark E., 2023. "Opioids and the labor market," Labour Economics, Elsevier, vol. 85(C).
    3. Martijn van Hasselt & Christopher R. Bollinger & Jeremy W. Bray, 2022. "A Bayesian approach to account for misclassification in prevalence and trend estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 351-367, March.
    4. Lena Edlund & Cecilia Machado, 2019. "It's the Phone, Stupid: Mobiles and Murder," NBER Working Papers 25883, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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