Escalating costs of self-injury mortality in the 21st century United States: an interstate observational study.

BACKGROUND: Estimating the economic costs of self-injury mortality (SIM) can inform health planning and clinical and public health interventions, serve as a basis for their evaluation, and provide the foundation for broadly disseminating evidence-based policies and practices. SIM is operationalized as a composite of all registered suicides at any age, and 80% of drug overdose (intoxication) deaths medicolegally classified as 'accidents,' and 90% of corresponding undetermined (intent) deaths in the age group 15 years and older. It is the long-term practice of the United States (US) Centers for Disease Control and Prevention (CDC) to subsume poisoning (drug and nondrug) deaths under the injury rubric. This study aimed to estimate magnitude and change in SIM and suicide costs in 2019 dollars for the United States (US), including the 50 states and the District of Columbia. METHODS: Cost estimates were generated from underlying cause-of-death data for 1999/2000 and 2018/2019 from the US Centers for Disease Control and Prevention's (CDC's) Wide-ranging ONline Data for Epidemiologic Research (WONDER). Estimation utilized the updated version of Medical and Work Loss Cost Estimation Methods for CDC's Web-based Injury Statistics Query and Reporting System (WISQARS). Exposures were medical expenditures, lost work productivity, and future quality of life loss. Main outcome measures were disaggregated, annual-averaged total and per capita costs of SIM and suicide for the nation and states in 1999/2000 and 2018/2019. RESULTS: 40,834 annual-averaged self-injury deaths in 1999/2000 and 101,325 in 2018/2019 were identified. Estimated national costs of SIM rose by 143% from $0.46 trillion to $1.12 trillion. Ratios of quality of life and work losses to medical spending in 2019 US dollars in 2018/2019 were 1,476 and 526, respectively, versus 1,419 and 526 in 1999/2000. Total national suicide costs increased 58%-from $318.6 billion to $502.7 billion. National per capita costs of SIM doubled from $1,638 to $3,413 over the observation period; costs of the suicide component rose from $1,137 to $1,534. States in the top quintile for per capita SIM, those whose cost increases exceeded 152%, concentrated in the Great Lakes, Southeast, Mideast and New England. States in the bottom quintile, those with per capita cost increases below 70%, were located in the Far West, Southwest, Plains, and Rocky Mountain regions. West Virginia exhibited the largest increase at 263% and Nevada the smallest at 22%. Percentage per capita cost increases for suicide were smaller than for SIM. Only the Far West, Southwest and Mideast were not represented in the top quintile, which comprised states with increases of 50% or greater. The bottom quintile comprised states with per capita suicide cost increases below 24%. Regions represented were the Far West, Southeast, Mideast and New England. North Dakota and Nevada occupied the extremes on the cost change continuum at 75% and - 1%, respectively. CONCLUSION: The scale and surge in the economic costs of SIM to society are large. Federal and state prevention and intervention programs should be financed with a clear understanding of the total costs-fiscal, social, and personal-incurred by deaths due to self-injurious behaviors.

Association of State Social and Environmental Factors With Rates of Self-injury Mortality and Suicide in the United States.

Importance: Self-injury mortality (SIM) combines suicides and the preponderance of drug misuse-related overdose fatalities. Identifying social and environmental factors associated with SIM and suicide may inform etiologic understanding and intervention design. Objective: To identify factors associated with interstate SIM and suicide rate variation and to assess potential for differential suicide misclassification. Design, Setting, and Participants: This cross-sectional study used a partial panel time series with underlying cause-of-death data from 50 US states and the District of Columbia for 1999-2000, 2007-2008, 2013-2014 and 2018-2019. Applying data from the Centers for Disease Control and Prevention, SIM includes all suicides and the preponderance of unintentional and undetermined drug intoxication deaths, reflecting self-harm behaviors. Data were analyzed from February to June 2021. Exposures: Exposures included inequity, isolation, demographic characteristics, injury mechanism, health care access, and medicolegal death investigation system type. Main Outcomes and Measures: The main outcome, SIM, was assessed using unstandardized regression coefficients of interstate variation associations, identified by the least absolute shrinkage and selection operator; ratios of crude SIM to suicide rates per 100 000 population were assessed for potential differential suicide misclassification. Results: A total of 101 325 SIMs were identified, including 74 506 (73.5%) among males and 26 819 (26.5%) among females. SIM to suicide rate ratios trended upwards, with an accelerating increase in overdose fatalities classified as unintentional or undetermined (SIM to suicide rate ratio, 1999-2000: 1.39; 95% CI, 1.38-1.41; 2018-2019: 2.12; 95% CI, 2.11-2.14). Eight states recorded a SIM to suicide rate ratio less than 1.50 in 2018-2019 vs 39 states in 1999-2000. Northeastern states concentrated in the highest category (range, 2.10-6.00); only the West remained unrepresented. Least absolute shrinkage and selection operator identified 8 factors associated with the SIM rate in 2018-2019: centralized medical examiner system (ß = 4.362), labor underutilization rate (ß = 0.728), manufacturing employment (ß = -0.056), homelessness rate (ß = -0.125), percentage nonreligious (ß = 0.041), non-Hispanic White race and ethnicity (ß = 0.087), prescribed opioids for 30 days or more (ß = 0.117), and percentage without health insurance (ß = -0.013) and 5 factors associated with the suicide rate: percentage male (ß = 1.046), military veteran (ß = 0.747), rural (ß = 0.031), firearm ownership (ß = 0.030), and pain reliever misuse (ß = 1.131). Conclusions and Relevance: These findings suggest that SIM rates were associated with modifiable, upstream factors. Although embedded in SIM, suicide unexpectedly deviated in proposed social and environmental determinants. Heterogeneity in medicolegal death investigation processes and data assurance needs further characterization, with the goal of providing the highest-quality reports for developing and tracking public health policies and practices.

The iatrogenic epidemic of prescription drug abuse: county-level determinants of opioid availability and abuse.

BACKGROUND: Opioid use and abuse in the United States continues to expand at an alarming rate. In this study, we examine the county-level determinants of the availability and abuse of prescription opioids to better understand the socio-ecological context, and in particular the role of the healthcare delivery system, on the prescription drug abuse epidemic. METHODS: We use community-level information, data from Indiana's prescription drug monitoring program in 2011, and geospatial regression methods to identify county-level correlates of the availability and abuse of prescription opioids among Indiana's 92 counties. RESULTS: The findings suggest that access to healthcare generally, and to dentists and pharmacists in particular, increases the availability of prescription opioids in communities, which, in turn, is associated with higher rates of opioid abuse. CONCLUSIONS: The results suggest that the structure of the local healthcare system is a major determinant of community-level access to opioids adding to a growing body of evidence that the problem of prescription opioid abuse is, at least in part, an "iatrogenic epidemic."

Occupational correlates of smoking among urban transit operators: a prospective study.

BACKGROUND: Workers in blue-collar and service occupations smoke at higher rates than workers in white-collar and professional occupations. Occupational stress may explain some of the occupational class differences in smoking and quitting behavior. The purpose of this study is to investigate the contribution of occupational factors to smoking behavior over a ten year period among a multiethnic cohort of urban transit operators, while accounting for demographic factors and alcohol. METHODS: The sample consists of 654 San Francisco Municipal Railway (MUNI) transit operators who participated in two occupational health studies and biennial medical examinations during 1983-85 and 1993-95. Workers who had initiated, increased, or maintained their smoking over the ten year period were compared to workers who remained non-smokers. Occupational factors included self-rated frequency of job problems (e.g., difficulties with equipment, passengers, traffic), job burnout (i.e., the emotional exhaustion subscale of the Maslach Burnout Inventory), time needed to unwind after work, and years employed as a transit operator. A series of logistic regression models were developed to estimate the contribution of occupational factors to smoking behavior over time. RESULTS: Approximately 35% of the workers increased, initiated, or maintained their smoking over the ten-year period. Frequency of job problems was significantly associated with likelihood of smoking increase, initiation, or maintenance (OR = 1.30; 95% CI 1.09, 1.55). Black operators were significantly more likely to have smoked over the ten-year period compared to operators in other racial/ethnic groups. CONCLUSION: Understanding the role of work-related stress vis-à-vis smoking behavior is of critical importance for crafting workplace smoking prevention and cessation interventions that are applicable to blue-collar work settings, and for developing policies that mitigate occupational stress.

Temporal changes in the spatial pattern of disease rates incorporating known risk factors.

Examining the geographical pattern of temporal changes in infant mortality rates illustrates the methodological problems of documenting and understanding temporal changes in any spatial pattern of disease. Early research on geographical differences in infant mortality rates showed strong ecological correlations with socio-economic factors such as poverty rates. More recent research established relationships between individual-level socio-economic values and probabilities of death. With geographic information available at the level of individuals, it is possible to estimate the probabilities of death on a person-by-person basis from knowledge of the relationships between individual factors and socio-economic measures. These estimated probabilities provide an expected geographic pattern of deaths. The difference between the observed spatial pattern and the expected pattern is the remaining spatial variation adjusted for this knowledge. For the study area, individual factors and some socio-economic measures were available for each year of the study period. Using data from the Iowa Birth Defects Registry and the Iowa Department of Public Health (USA), I tested the stability and continuity of these cross-sectional relationships and investigated whether any temporal lags in these variables relate to the unexplained spatial variations in infant mortality rates that remain. I accounted for the 'Change of Support Problem' [Gotway C. A. & Young L. J. (2002). Combining incompatible spatial data. Journal of the American Statistical Association, 97458, 632-648] inherent in frame-based geographical analysis. The analysis involved a generalized linear model (GLM) to estimate individual risks and a Monte Carlo simulation model to generate the non-linear probability density functions for disease rates whose densities are theoretically intractable. Results show the temporal changes in the observed spatial pattern and the expected spatial pattern differ by geographic location. In conclusion such differences are the result of a combination of unexplained place-based risk and unmeasured individual risks.