Age and generational patterns of overdose death risk from opioids and other drugs


The ongoing substance misuse epidemic in the United States is complex and dynamic and should be approached as such in the development and evaluation of policy1. Drug overdose deaths (largely attributable to opioid misuse) in the United States have grown exponentially for almost four decades, but the mechanisms of this growth are poorly understood2. From analysis of 661,565 overdose deaths from 1999 to 2017, we show that the age-specific drug overdose mortality curve for each birth-year cohort rises and falls according to a Gaussian-shaped curve. The ascending portion of each successive birth-year cohort mortality curve is accelerated compared with that of all preceding birth-year cohorts. This acceleration can be attributed to either of two distinct processes: a stable peak age, with an increasing amplitude of mortality rate curves from one birth-year cohort to the next; or a youthward shift in the peak age of the mortality rate curves. The overdose epidemic emerged and increased in amplitude among the 1945–1964 cohort (Baby Boomers), shifted youthward among the 1965–1980 cohort (Generation X), and then resumed the pattern of increasing amplitude in the 1981–1990 Millennials. These shifting age and generational patterns are likely to be driven by socioeconomic factors and drug availability, the understanding of which is important for the development of effective overdose prevention measures.

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Fig. 1: Hexamaps illustrating the age and generational structure of overdose deaths from 1979 to 2017.
Fig. 2: Rapid rise in age-specific overdose mortality curves by birth-year cohort.
Fig 3: Birth-year specific overdose mortality follows Gaussian curves.
Fig. 4: Three phases of overdose deaths revealed by plotting of the estimated peak age of overdose mortality versus the estimated peak amplitude of the overdose mortality rate, for all fifty-one birth-year cohorts 1940–1990.

Data availability

Multiple Cause of Death Data from the Centers for Disease Control and Prevention is available by request at Population demographics from the US Census is available at The code for creating the hexamaps is provided in ref. 5. In addition, all the equations to reproduce the quadratic fits and the transformation equations to the set of Gaussian curves are presented in the online Methods. The numerical results of the quadratic fits are presented in Supplementary Table 1.


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This study was in part supported by National Institutes of Health/National Center for Advancing Translational Sciences grant no. 1KL2TR0001856 (H.J.), and Robert Wood Johnson Foundation grant no. 72858 (J.B. and D.S.B.).

Author information




D.S.B. and H.J. conceived of the study, H.J. and J.M.B. conducted the data analyses, and H.J., D.S.B., J.M.B., D.R.S. and M.S.R. all contributed to the interpretation of results and writing of the manuscript.

Corresponding authors

Correspondence to Hawre Jalal or Donald S. Burke.

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The authors declare no competing interests.

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Peer review information Jennifer Sargent was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Results of age–period–cohort analysis from the first Poisson log-linear regression model.

Black horizontal line represents no effect, the black curves represent the estimated effect and the orange and green shaded area represent the associated confidence interval. a, b and c show the age, period and cohort deviations which reveal significant statistical deviation for most ages, periods and cohorts (since the confidence interval does not cover 0). The net drift from this analysis was 8.23% per year CI = (8.17, 8.30) and is also statistically significant since the confidence interval does not cover 0 (D). d also shows statistically significant differences in the age-specific local drifts against the net drift which range between 4% to 11%. e shows the cross-sectional and longitudinal age curves for overdose mortality. The cross-sectional curve reveals the age-specific mortality rates for the reference period of p0 = 2000, and the longitudinal age curve reveals the age-specific mortality rate for the reference cohort of c0 = 1960. The clear divergence of these two age curves indicates important cohort effects that can also be revealed from the net drift. (F) and (G) reveal the period and cohort rate ratios of mortality rate against the reference period (p0 = 2000) and reference cohort (c0 = 1960), respectively.

Extended Data Fig. 2 Hexamaps showing the reproducibility of overdose deaths from the Gaussian curves.

The raw drug overdose mortality rates are shown in a and a reconstruction from the quadratic equation Gaussian curves is shown in b. Both the original data plot and the reconstructed plot are limited to birth-year cohorts after 1940.

Extended Data Fig. 3 Relationship between the peak age for overdose mortality and peak overdose mortality rates.

The purple line indicates the estimated peak age and overdose mortality for birth-years from 1940 through 1990. Decennial cohorts are marked with a red circle and labeled. The horizontal and vertical blue lines represent the 95% confidence interval of the estimated peak age for overdose mortality and peak overdose mortality rate, respectively.

Supplementary information

Reporting Summary

Supplementary Information

Supplementary Table 1.

Supplementary Video 1

Fitted age-specific mortality rate curves by single birth-year cohorts from 1940 to 1990 are displayed in sequence. For each birth-year cohort, the red data points and lines represent the observed data, the solid blue lines represent the fitted Gaussian curve and dotted blue lines represent the projected curve. The shaded area around each line represents the confidence interval.

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Jalal, H., Buchanich, J.M., Sinclair, D.R. et al. Age and generational patterns of overdose death risk from opioids and other drugs. Nat Med 26, 699–704 (2020).

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