Invited commentary: Motivating better methods-and better data collection-for measuring prevalence of drug misuse.

The United States continues to suffer a drug overdose crisis that has resulted in over 100,000 deaths annually since 2021. Despite decades of attention, estimates of the prevalence of drug use at the spatiotemporal resolutions necessary for resource allocation and intervention evaluation are lacking. Current approaches to measure prevalence of drug use, such as population surveys, capture-recapture, and multiplier methods, have significant limitations. Santaella-Tenorio et al. (Am J Epidemiol. XXXX;XXX(XX):XXXX-XXXX)) use a novel joint Bayesian spatiotemporal modeling approach to estimate county-level opioid misuse prevalence in New York state from 2007 to 2018 and identify significant intra-state variation. By leveraging five data sources and simultaneously modeling different opioid-related outcomes - such as deaths, emergency department visits, and treatment visits - they obtain policy-relevant insights into the prevalence of opioid misuse and opioid-related outcomes at high spatiotemporal resolutions. This study provides future researchers with a sophisticated modeling approach that allows them to incorporate multiple data sources in a rigorous statistical framework. The limitations of the study reflect the constraints of the broader field and underscores the importance of enhancing current surveillance with better, newer, and more timely data that is both standardized and easily accessible to inform public health policies and interventions.

Youth Experiencing Parental Death Due to Drug Poisoning and Firearm Violence in the US, 1999-2020.

Importance: Youth (those aged <18 years) parental death has been associated with negative health outcomes. Understanding the burden of parental death due to drug poisoning (herein, drugs) and firearms is essential for informing interventions. Objective: To estimate the incidence of youth parental death due to drugs, firearms, and all other causes. Design, Setting, and Participants: This cross-sectional observational study was conducted using vital registration, including all US decedents, and census data from January 1990 through December 2020. Data were analyzed from May 30, 2023, to March 28, 2024. Exposures: Parental death due to drug poisoning or firearms. Main Outcomes and Measures: A demographic matrix projection model was used to estimate the number and incidence of youth experiencing parental death, defined as the death of 1 or more parents, per 1000 population aged less than 18 years. Analyses evaluated parental deaths by drugs, firearms, and all other causes from 1999 through 2020 by race and ethnicity. Results: Between 1999 and 2020, there were 931 785 drug poisoning deaths and 736 779 firearm-related deaths with a mean (SD) age of 42.6 (16.3) years. Most deaths occurred among males (73.8%) and White decedents (70.8%) followed by Black (17.5%) and Hispanic (9.5%) decedents. An estimated 759 000 (95% CI, 722 000-800 000) youth experienced parental death due to drugs and an estimated 434 000 (95% CI, 409 000-460 000) youth experienced parental death due to firearms, accounting for 17% of all parental deaths. From 1999 to 2020, the estimated number of youth who experienced parental death increased 345% (95% CI, 334%-361%) due to drugs and 39% (95% CI, 37%-41%) due to firearms compared with 24% (95% CI, 23%-25%) due to all other causes. Black youth experienced a disproportionate burden of parental deaths, based primarily on firearm deaths among fathers. In 2020, drugs and firearms accounted for 23% of all parental deaths, double the proportion in 1999 (12%). Conclusions and Relevance: Results of this modeling study suggest that US youth are at high and increasing risk of experiencing parental death by drugs or firearms. Efforts to stem this problem should prioritize averting drug overdoses and firearm violence, especially among structurally marginalized groups.

Sociodemographic characteristics of missing data in digital phenotyping.

The ubiquity of smartphones, with their increasingly sophisticated array of sensors, presents an unprecedented opportunity for researchers to collect longitudinal, diverse, temporally-dense data about human behavior while minimizing participant burden. Researchers increasingly make use of smartphones for "digital phenotyping," the collection and analysis of raw phone sensor and log data to study the lived experiences of subjects in their natural environments using their own devices. While digital phenotyping has shown promise in fields such as psychiatry and neuroscience, there are fundamental gaps in our knowledge about data collection and non-collection (i.e., missing data) in smartphone-based digital phenotyping. In this meta-study using individual-level data from six different studies, we examined accelerometer and GPS sensor data of 211 participants, amounting to 29,500 person-days of observation, using Bayesian hierarchical negative binomial regression with study- and user-level random intercepts. Sensitivity analyses including alternative model specification and stratified models were conducted. We found that iOS users had lower GPS non-collection than Android users. For GPS data, rates of non-collection did not differ by race/ethnicity, education, age, or gender. For accelerometer data, Black participants had higher rates of non-collection, but rates did not differ by sex, education, or age. For both sensors, non-collection increased by 0.5% to 0.9% per week. These results demonstrate the feasibility of using smartphone-based digital phenotyping across diverse populations, for extended periods of time, and within diverse cohorts. As smartphones become increasingly embedded in everyday life, the insights of this study will help guide the design, planning, and analysis of digital phenotyping studies.

Assessment of Changes in the Geographical Distribution of Opioid-Related Mortality Across the United States by Opioid Type, 1999-2016.

Importance: As the opioid epidemic evolves, it is vital to identify changes in the geographical distribution of opioid-related deaths, and the specific opioids to which those deaths are attributed, to ensure that federal and state public health interventions remain appropriately targeted. Objective: To identify changes in the geographical distribution of opioid-related mortality across the United States by opioid type. Design, Setting, and Participants: Cross-sectional study using joinpoint modeling and life table analysis of individual-level data from the National Center for Health Statistics on 351 630 US residents who died from opioid-related causes from January 1, 1999, to December 31, 2016, for all of the United States and the District of Columbia. The analysis was conducted from September 6 to November 23, 2018. Exposures: Deaths involving any opioid, heroin, synthetic opioids, and natural and semisynthetic opioids. Main Outcomes and Measures: Opioid-related mortality rate, annual percent change in the opioid-related mortality rate, and life expectancy lost at age 15 years by state and opioid type. Results: From 1999 to 2016, a total of 231 264 men and 120 366 women died from opioid-related causes across the whole United States. Sixty-six observations were removed owing to missing data on age; therefore, 351 564 US residents were included in this study. The mean (SD) age at death was 39.8 (12.5) years for men and was 43.5 (12.9) years from women. Opioid-related mortality rates, especially from synthetic opioids, rapidly increased in all of the eastern United States. In most states, mortality associated with natural and semisynthetic opioids (ie, prescription painkillers) remained stable. In contrast, 28 states had mortality rates from synthetic opioids that more than doubled every 2 years (ie, annual percent change, ≥41%), including 12 with high mortality rates from synthetic opioids (>10 per 100 000 people). Among these 28 states, the mortality rate from natural and semisynthetic opioids ranged from 2.0 to 18.7 per 100 000 people (with a mean mortality rate of 6.0 per 100 000 people). The District of Columbia had the fastest rate of increase in mortality from opioids, more than tripling every year since 2013 (annual percent change, 228.3%; 95% CI, 169.7%-299.6%; P < .001), and a high mortality rate from synthetic opioids in 2016 (18.8 per 100 000 people); the mortality rate from natural and semisynthetic opioids was 6.9 per 100 000 people. Nationally, overall opioid-related mortality resulted in 0.36 years of life expectancy lost in 2016, which was 14% higher than deaths due to firearms and 18% higher than deaths due to motor vehicle crashes; 0.17 years of the life expectancy lost was due specifically to synthetic opioids. In 2016, New Hampshire and West Virginia lost more than 1 year of life expectancy due to opioid-related mortality. Conclusions and Relevance: Opioid-related mortality, particularly mortality associated with synthetic opioids, has increased in the eastern United States. These findings indicate that policies focused on reducing opioid-related deaths may need to prioritize synthetic opioids and rapidly expanding epidemics in northeastern states and consider the potential for synthetic opioid epidemics outside of the heroin supply.

Trends in Black and White Opioid Mortality in the United States, 1979-2015.

BACKGROUND: Recent research on the US opioid epidemic has focused on the white or total population and has largely been limited to data after 1999. However, understanding racial differences in long-term trends by opioid type may contribute to improving interventions. METHODS: Using multiple cause of death data, we calculated age-standardized opioid mortality rates, by race and opioid type, for the US resident population from 1979 to 2015. We analyzed trends in mortality rates using joinpoint regression. RESULTS: From 1979 to 2015, the long-term trends in opioid-related mortality for Earlier data did not include ethnicity so this is incorrect. It is all black and all white residents in the US. blacks and whites went through three successive waves. In the first wave, from 1979 to the mid-1990s, the epidemic affected both populations and was driven by heroin. In the second wave, from the mid-1990s to 2010, the increase in opioid mortality was driven by natural/semi-synthetic opioids (e.g., codeine, morphine, hydrocodone, or oxycodone) among whites, while there was no increase in mortality for blacks. In the current wave, increases in opioid mortality for both populations have been driven by heroin and synthetic opioids (e.g., fentanyl and its analogues). Heroin rates are currently increasing at 31% (95% confidence interval [CI] = 27, 35) per year for whites and 34% (95% CI = 30, 40) for blacks. Concurrently, respective synthetic opioids are increasing at 79% (95% CI = 50, 112) and 107% (95% CI = -15, 404) annually. CONCLUSION: Since 1979, the nature of the opioid epidemic has shifted from heroin to prescription opioids for the white population to increasing of heroin/synthetic deaths for both black and white populations. See video abstract at, http://links.lww.com/EDE/B377.