DO DEATHS OF DESPAIR MOVE TOGETHER? COUNTY-LEVEL MORTALITY CHANGES BY SEX AND URBANIZATION, 1990–2017

Edito r’s note: An invited commentary on this article appears on page 1172, and the authors' response is published on page 1175.

The “deaths of despair” (DOD) perspective has strongly influenced recent thought and discussions about US mortality trends (1–6). According to this perspective, increases in all-cause mortality rates among working-aged White Americans have been driven by alcohol-related deaths, drug-related deaths, and suicides, which are assumed to move together “both temporally and spatially” as “symptoms of the same underlying epidemic” (1, p. 15081). As a result, death rates from the separate causes of death (COD) are often summed into a single DOD measure because 1) they are believed to be outcomes of the same underlying social and economic causes; and 2) the separate COD trends are assumed to move together (1, 2). It is further argued that DOD trends cluster geographically, especially in rural White communities (4–6). However, on the first point, there is a dearth of research connecting key exposures—economic distress and individual despair—to these mortality outcomes, drawing concerns about attributing psychological distress to recent mortality changes (7). Further, trends in DOD mortality appear to be strongly associated with US Whites’ perceived loss of status rather than rising economic and psychological distress (8). Regarding point 2, researchers have also questioned the validity of analyzing a summed DOD rate given that the mortality trends differ substantively by sex (9) and the timing at which each COD began to increase (10), and because increases in the summed DOD rate overwhelmingly reflect increases in drug-related deaths (10, 11). In this research letter, we return to a central assumption of the DOD perspective, which is that the death rates from drug use, alcohol use, and suicide move together across time and place.

We estimated county-level associations between both levels and trends in age-standardized mortality rates from drug-related deaths, alcohol-related deaths, and suicides among US White men and women aged 20–65 years between the years 1990 and 2017. Our mortality data was obtained through the National Association for Public Health Statistics and Information System, and we considered the associations separately by counties’ level of urbanization using Economic Research Service county typology codes to indicate rural, urban, or mix status (code available in Web Appendices 1–4, available at https://doi.org/10.1093/aje/kwab015).

First, we present correlations in mortality change scores between 1990–1991 and 2016–2017 in line with the seminal DOD study that examined change scores between 1999 and 2013 (1). Table 1 reports these correlations by sex, cause of death, and urbanization (see Web Figure 1 and Web Appendix 5 for 3-way scatterplots and code). The primary takeaway from this table is that county-level mortality changes in separate DOD causes were not associated with each other. In fact, contrary to a rural despair narrative (4–6), the only statistically significant associations are observed in urban counties, and these are substantively weak.

Table 1.

Correlations in County-Level “Deaths of Despair” by Sex, Cause of Death, and Urbanization, United States, 1990–2017

Pair for Correlation in Mortality Change Score a	Urban Counties		Mixed Counties		Rural Counties
	Male	Female	Male	Female	Male	Female
Drug, Alcohol	0.037	0.119b	0.048	0.041	−0.013	0.044
Drug, Suicide	0.024	0.030	0.026	0.049	0.006	0.050
Alcohol, Suicide	0.130b	0.109b	−0.051	−0.029	0.036	−0.022

^a Correlations in mortality change scores between 1990–1991 and 2016–2017.

^b Statistically significant correlation at P < 0.01.

Next, we illustrate that the findings presented in Table 1 are robust to alternative specifications of time (see Web Appendix 6, Web Table 1, Web Figure 2, Web Appendix 7, and Web Figure 3 for additional sensitivity checks). Figure 1 presents year-over-year correlations between these causes of death according to sex to better understand associations in annual DOD mortality trends. Again, the general finding remains the same; the trends in these causes of death appear unrelated to one another at the county level. For non-Hispanic White men and women both, the average correlation between any 2 causes of death does not exceed 0.1, with the highest single-year correlation just 0.24 for female drug and alcohol-related mortality in 1997.

Figure 1.

Year-over-year correlations in county-level cause-specific mortality in the United States, 1990–2017 for White women (A) and White men (B). Average correlations for women: drug and suicide = 0.051; drug and alcohol = 0.075; alcohol and suicide = 0.033. Average correlations for men: drug and suicide = 0.064; drug and alcohol = 0.099; alcohol and suicide = 0.084.

Taken together, Table 1 and Figure 1 provide little to no evidence to support the claim that these separate COD among white Americans have moved together “temporally or spatially” (1, 2). This simple finding complicates the use of a summed DOD death rate and should encourage researchers to explore how the drivers of these mortality trends might differ by cause and place. Although mortality trends from the separate causes of death might be theoretically linked to a shared exposure (12), findings here suggest that the mortality outcomes themselves do not appear to be empirically related. Additional research is needed to better understand the important within-group heterogeneity that goes unobserved when researchers analyze a summed DOD death rate.