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Investigating the Rise (and Fall) of Young Black Male Suicide in the United States, 1982–2001

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Abstract

Scholars and public health officials alike have expressed significant concern over the dramatic growth in suicide among young Black males. Work in this area has focused primarily on the 1980s and early 1990s as key evidence of this concern. In the current study, we use a longer time series from 1982 to 2001 to examine exactly what these suicide trends look like as well as how and why they vary across US cities. The findings show that trends are more complex than originally perceived, that despite an average national trend there is significant variation in suicide trajectories across cities, that the general rise in rates into the early 1990s was followed by a substantial decline by the turn of the century, and that concentrated disadvantage and gun availability emerge as important predictors of differences in trends across cities.

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Notes

  1. For analysis of national-level trends in Black male suicide levels from 1947 to 1998 and the impact of educational attainment on such trends, see Fernquist (2004).

  2. See Wray et al. (2011) for a discussion on the sociological explanations of suicide in historical context and Stack (2000a, b) for extended reviews of the sociological suicide literature.

  3. See Goldston et al. (2008) for extended discussion on the racial and ethnic differences in the rates of suicidal behaviors and the importance of considering cultural and social influences for different groups.

  4. “City” is based on Census “places” which were designated as cities in the 1990 census.

  5. Azrael et al. (2004, p. 49) document correlations of 0.90 between FS/S and state-level measures of household firearms ownership found in the Behavioral Risk Factor Surveillance Systems and 0.93 between FS/S and regional measures of household firearms ownership generated from General Social Survey data. Other measures of firearm availability found in the suicide literature, such as subscriptions to Guns and Ammo magazine and National Rifle Association membership, exhibited much weaker correlations with the survey-based measures (0.67 and 0.55 with the BRFSS, and 0.51 and −0.06 with the GSS).

  6. The concern has to do with potential bias stemming from two sources. Critics have suggested that using the same measure as a numerator or denominator on both sides of the equation may introduce bias into the model. This critique, however, has been refuted (Long 1979; Gibbs and Firebaugh 1990). These studies demonstrate that the potential for such bias is low, and even more unlikely when including multiple covariates in the analyses. The second concern is there will be correlated measurement error between multiple terms in the equation. We address this concern by regressing race-, gender-, and age-specific suicide counts on a measure of gun availability that comprised general, not race-, gender-, or age-specific, measures of suicide and homicide. Given our approach to creating the measure of gun availability (the use of multiple and general measures), we argue that there is little likelihood we have introduced correlated measurement error into the models.

  7. The 1990 and 2000 indicators are each based on 3-year averages (1989–1991 and 1999–2001) of FH/H and FS/S. Given data limitations, the 1980 indicator is based on a 2-year average starting in 1982 (1982–1983).

  8. We also explored using a latent growth mixture model to test whether there were distinctive classes of cities experiencing different patterns of suicide growth and decline (Nagin 1999; Muthen 2004; Muthen and Muthen 2000). The results of these models suggest only one underlying pattern or class.

  9. The quadratic model provided the best fit to the data (BIC = 28,387); the linear model is inaccurate and a cubic model did not provide any improvement in fit (BIC = 28,391).

  10. Fitting the quadratic model with random intercepts and slopes shows significant variability in the three parameters. The standard deviations (95% CI) for the intercepts, b 1, and b 2, are 18.7 (16.2–21.7), 4.8 (4.2–5.6), and 0.24 (0.21–0.28), respectively. Furthermore, adding the two random components provides a significant improvement over the model with simply a random intercept; the improvement in fit is LR χ 2 = 417 (df = 5).

  11. The quadratic model with random effects for the intercept and slopes captures the trends and demonstrates significant variability in the trajectories across cities; however, the quadratic form makes the interpretation of the relationship among urban characteristics and the growth/decline of suicide rates unwieldy and difficult to interpret. The rate of change at any point in time is implicitly a function of both parameters in the model, b 1j and b 2j , rather than a single parameter. For ease of interpretation, we approach modeling the curve using splines to capture basically a linear uptake in suicide in the early period and a linear decline in suicide in the latter part of the time series. This allows capturing the rise and fall observed in an analytical manner that permits relating the variation in change to a single parameter for the rise and a different single parameter for the fall, thus making interpretation straightforward.

  12. Defining where the point of rise/fall in suicide rates occurs for the spline formulation was approached by first estimating the quadratic model and calculating the point at which the rate of change in suicide for young Black males was 0, basically calculating the point at which the derivative of the quadratic with respect to year was 0, indicating the year prior to the fall. Taking the partial and setting it to 0 indicates that the inflection point occurs between 1992 and 1993. We then built the spline models using time points to either side of 1992 and 1993 and estimated the splines. Using BIC to distinguish the best-fitting spline, we determine that using the turning point at 1993 fits the data the best among the alternative splines. In all cases, there was significant variation across cities in the d 0j and d 1j parameters.

  13. Moving to the spline models to simplify the interpretation of how city characteristics relate to the rise and fall of suicide requires the assumption that all cities peaked at a given year, in this case 1993. We explored this assumption in three ways. First, we calculated the empirical Bayes estimates of the parameters in the quadratic model and derived the apex year for each city. This shows that 60 % of the cities have their apex falling between 1991 and 1995 and that another 15 % were inherently linear—no real apex is present, but this does not impact where one defines the spline’s break point. This suggests that 75 % of the cities have an apex close to 1993. Second, we varied where the apex occurred (at 1992, 1993, and 1994), and the results were consistent with the models we present. Third, we removed the middle years of the time series (1992, 1993, and 1994) and re-estimated the two models; again, the results were consistent with what we present. This sensitivity analysis suggests that the results are robust to the assumption of using 1993 as a common apex.

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Acknowledgment

Financial support for this research was provided by the Harry Frank Guggenheim Foundation.

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Authors and Affiliations

  1. Department of Sociology, University of Colorado, UCB 327, Boulder, CO, 80309, USA

    Tim Wadsworth

  2. University of California Irvine, Irvine, CA, USA

    Charis E. Kubrin

  3. University of Washington, Seattle, WA, USA

    Jerald R. Herting

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  1. Tim Wadsworth
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Correspondence to Tim Wadsworth.

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Wadsworth, T., Kubrin, C.E. & Herting, J.R. Investigating the Rise (and Fall) of Young Black Male Suicide in the United States, 1982–2001. J Afr Am St 18, 72–91 (2014). https://doi.org/10.1007/s12111-013-9256-3

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