opioid OD mortality increased with auto plant closing

 A recent article found a relationship between automotive assembly plant closings and opioid overdose mortality (see opioid mortality and closing auto plants jamaintmed2019 in dropbox, or doi:10.1001/jamainternmed.2019.5686)

Details:
-- a county-level comparison was done from 1999-2017 of adults in 112 manufacturing counties located in 30 commuting zones, mostly in the US South and Midwest
    -- at baseline in 1999, these 112 counties accounted for 2.7% of the total US population aged 18-65; and from 1999-2017, 3.4% of the total number of deaths from opioid overdose nationwide among this age group 
-- 29 manufacturing counties in 10 commuting zones had plant closures; 83 were unexposed to plant closures [exposed counties were defined as having a plant closure in the commuting zone of where they were located; commuting zones were the contiguous counties used to define local labor markets]
-- comparing areas with plant closures vs no closures:
    -- mean baseline (prior to plant closing) opioid overdose rates per 100,000 were similar in the exposed vs unexposed counties (0.9 vs 1.0)
    -- 61% were working age adults in both groups
    -- county level unemployment rates were 3.2% in both groups
    -- 12% of adults completed college in both groups
    -- median income was $45,000 in both groups
    -- 4.1 vs 3.7% of households were below 100% of the federal poverty line
    -- 85% vs 91% of adults were non-Hispanic white persons 

Results:
-- comparing counties with and without auto plant closures:
    -- 5 years after plant closure: mortality rates from opioid overdose deaths increased by 8.6 per 100K (2.6-14.6), p=0.006, representing an 85% increase over the mortality rate of 12 deaths/100K in the unexposed counties at the same time point
    -- stratified by age, sex, race/ethnicity, the highest death rate was in non-Hispanic white people:
        -- non-Hispanic white men aged 13 to 34: 20.1 deaths/100K (8.8-31.3), p=0.001
        -- non-Hispanic white men aged 35 to 65: 12.8 deaths/100K (5.7-20.0), p=0.001
        -- non-Hispanic white women aged 18-34: 6.4 deaths/100K  (0.4-12.3), p=0.04; no significant difference in older white women
        -- not enough non-white people to have a significant association, though the trend seemed to be of a lower magnitude
-- the increased differences between exposed and unexposed counties began within 1 year of plan closure and continued to increase linearly til the 5^th year and then leveled out at about an increase of 8/100K
-- similar patterns were found for prescription vs illicit drug overdose mortality (though younger people had more illicit opioids and older ones had more prescription opioids)
-- opioid overdose mortality estimates in non-manufacturing counties did not statistically significantly change during the same time period
-- secondary outcome of overall drug overdose mortality: the pattern and magnitude of these estimates after 5 years of exposure were similar to the above ones for opioids, with 9.5 excess deaths per 100,000 (4.8-14.1), p<0.001
-- no difference in patterns of migration rates associated with the plant closures (ie, above findings were not skewed by differential outmigration)

Commentary:
-- as widely noted, opioid-related overdose mortality has increased dramatically in the past 2 decades, especially among working age adults
    -- efforts overall have been targeted at physician prescribing behavior and increased availability of synthetic opioids (a focus on reducing the supply of opiates)
    -- several authors have argued that decreased economic opportunities are important factors leading to increased demand for opioids, “death of despair”, though studies looking at the association between opioid overdose mortality and unemployment or income have had mixed results.
    -- however, studies looking at changes in employment opportunities (e.g. from changes in international trade policy) have had strong associations with drug overdose mortality. And, this current study reflects changes in employment opportunities, since auto plant closings create significant disruption in peoples’ cultural, psychological, and economic changes in their lives
    -- this study found a pretty impressive (?depressive) 85% increase in opioid mortality, which seemed to increase linearly for 5 years, found only in those counties with auto plant closures, and suggesting that declining economic opportunity was indeed the likely driver
    -- many people abandoned by the auto industry were either unable to find work or only found work at significantly lower pay (though their costs of living/payments for housing likely did not change much), though this was not assessed in this study [one major issue here is that unions have been largely decimated over time in the US, exacerbating the changes in workers’ wages]
    -- and, even in areas where manufacturing has returned to the US, this has mostly been by developing automated plants where the levels of employment/pay are much lower than previously
-- one potentially important side issue is that many of the plant closings were in the Midwest and South, areas of the country that overall have less accessible health care/lower health insurance rates.
-- there were several older studies from the 1960s and 1970s that assessed clinical outcomes of workers who had lost their jobs (in some cases, interviewing workers in advance of an anticipated upcoming factory closing, then following workers for some time afterwards), finding increased cardiac symptoms, musculoskeletal symptoms, and lots of increased anxiety/depression.
-- the authors of the current study also comment on the potential utility of assessing other causes of death historically associated with economic hardship, eg suicide and alcoholic liver disease (more about these increases currently in an upcoming blog).  There certainly are abundant studies about these other events, and assessing them would help reinforce their conclusions about economic hardship-associated deaths.

--there are several limitations to the above study:
    -- as an observational study, we cannot attribute causality (there could be unmeasured confounders that actually explain the differences found). and there are very limited specific granular data about the patients who took the opioids (what were their medical/psych comorbidities, what social resources were provided to assist them during this very stressful process, how did the loss of the auto plants affect the overall communities, were those who overdosed in fact prior employees or more indirectly affected by the plant closings, etc)
    -- reliance on the information in death certificates is not necessarily accurate (errors in coding, perhaps coding more opioid-related deaths in higher risk communities and thereby exaggerating the association??)

        --several articles have looked at death certificates and compared them with autopsy findings, typically with about a 50% mismatch

        -- and, as a community-based clinician, we receive death certificates from funeral homes requiring diagnoses, even for patients who have not been seen for many months. it really amounts to guesswork for many of them, and inference in many others (the person had pretty severe COPD, so we write "cardiorespiratory arrest from COPD" as the cause of death. Fraught with very likely errors....)

    -- unclear whether these results are generalizable to other settings of sudden changes of worksites.  is it related to city size? the numbers of other large industries? was their a differential effect if people could find other jobs?

so, this study does reinforce that when we look at opioid use overall (and overdose deaths), we should focus not just on the supply side (what we are doing as clinicians to decrease the availability of prescription opioids) but also at the demand side (what dysfunctional social systems do we have that create the social basis for the current opioid crisis). And this latter part is undoubtedly the most important and difficult part. we clinicians are only part of the supply issue (the other being non-prescription opiates coming into the community) and the inroads made by clinicians has so far resulted in only small but significant changes in decreasing opiate prescriptions. though we should certainly continue to do whatever we can to decrease these prescriptions, we should also do whatever we can to help improve the underlying social conditions that are so intricately tied into the current opioid crisis…

geoff​

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