Objectives Elevated mortality has been observed among individuals with opioid use disorder (OUD) treated in addiction specialty clinics or programs. Information about OUD patients in general healthcare settings is needed in light of the current effort to integrate addiction services into primary healthcare systems. This study examined mortality rates, causes of death, and associated risk factors among patients with OUD in a large general healthcare system. Methods Mortality data were linked with electronic health records of 2,576 OUD patients cared for in a large university health system from 2006–2014. Results There were 465 deaths confirmed (18.1% of the study participants), corresponding to a crude mortality rate of 48.6 per 1000 person-years and standardized mortality ratio of 10.3 (95% CI, 9.4–11.3). Drug overdose and disorder (19.8%), cardiovascular diseases (17.4%), cancer (16.8%), and infectious diseases (13.5%, including 12% hepatitis C virus [HCV]) were the leading causes of death. HCV (HR: 1.99; 95% CI, 1.62– 2.46) and alcohol use disorder (HR: 1.27; 95% CI, 1.05–1.55) were two clinically important indicators of overall mortality risk. Tobacco use disorder (AHR: 2.58; 95% CI, 1.60–4.17) was associated with increased risk of cardiovascular death, HCV infection (AHR: 2.55; 95% CI, 1.52–4.26) with cancer mortality risk, and HCV (AHR: 1.92; 95%CI, 1.03–3.60) and alcohol use disorder (AHR: 5.44; 95% CI, 2.95–10.05) with liver-related mortality risk. Conclusions Patients with OUD in a general healthcare system demonstrated alarmingly high morbidity and mortality, which challenges health care systems to find innovative ways to identify and treat patients with substance use disorder.

Aims This study examined the longitudinal association between reductions in cannabis use and changes in anxiety, depression, sleep quality, and quality of life. Methods Secondary analyses were conducted based on data from a cannabis use disorder medication trial in 302 adults (ages 18–50). Changes in symptoms of anxiety and depression, sleep quality, and quality of life were assessed in relation to changes in cannabis use during the 12-week trial of treatment. Results Based on the slope of individual cannabis use trajectory, the sample was classified into two groups (Cannabis Use Reduction, n=152 vs. Cannabis Use Increase, n=150) which was included as a binary covariate in subsequent modeling. Controlling for demographics (age, gender, race/ethnicity), treatment condition, and time-varying tobacco and alcohol use, separate latent growth curve models showed a significant association between the Cannabis Use Reduction group and improvement (i.e., lower values in slope) in anxiety (β= −.09, SE=0.04; p<0.05), depression (β= −0.11, SE=0.04; p<0.01), and sleep quality (β= −0.07, SE=0.03; p<0.05) over the observation period, but not in quality of life. Conclusions These results indicate a longitudinal relationship between reductions in cannabis use and improvements in anxiety, depression, and sleep quality. Clinicians treating patients with co-occurring cannabis use and problems with anxiety, depression, or sleep quality should attend to cannabis use reduction as a component of treatment.

Purpose To examine characteristics associated with disparities in digital access (i.e., access to high‐speed Internet via a computer or smartphone) in American rural and urban households given that digital access has a direct impact on access to telemedicine‐based services. Methods Using the 2019 American Community Survey, we analyzed the proportions of geographic area, race/ethnicity, and socioeconomic status according to device and high‐speed Internet access. Maximum likelihood logit estimators estimated how these factors influenced device and high‐speed Internet access. Findings Of 105,312,959 households, 32.29% were without a desktop or laptop computer with high‐speed Internet (WDW), 21.51% were without a smartphone with a data plan for wireless Internet (WSW), and 14.02% were without any digital access (WDA). Nonmetropolitan households were significantly more likely to be WDA than metropolitan households (odds ratio [OR] = 1.87; 95% confidence interval [CI]: 1.83‐1.91). Relative to non‐Hispanic Whites, non‐Hispanic Blacks (OR = 1.60; 95% CI: 1.56‐1.64), American Indian or Alaska natives (OR = 2.00; 95% CI: 1.82‐2.19), or Hispanics (OR = 1.70; 95% CI: 1.66‐1.74) were significantly more likely to be WDA. When compared to households with private health insurance coverage, households WDA were significantly more likely to have no insurance (OR = 2.44; 95% CI: 2.36‐2.53) or public insurance coverage (OR = 3.78; 95% CI: 3.70‐3.86). Households with any digital access reported higher income and more family members living at home. Using the same predictors, similar findings were reported for households WDW or WSW. Conclusions Significant disparities in digital access exist among nonmetropolitan households, racial/ethnic minority households, and lower‐income households. The lack of digital access has implications for the accessibility of health care services via telemedicine and thus could exacerbate health disparities.

Opioid use disorder (OUD) is a chronic, relapsing condition with severe negative health consequences. Previous studies have reported that 5-year opioid abstinence is a good predictor of reduced likelihoods of relapse, but factors that shape long-term opioid abstinence are poorly understood. The present study is based on data from a prospective study of 699 adults with OUD who had been randomized to either methadone or buprenorphine/naloxone and who were followed for at least 5 years. During the 5 years prior to the participants' last follow-up interview, 232 (33.2%) had achieved 5-year abstinence from heroin. Of those 232, 145 (20.7% of the total) had remained abstinent from both heroin and other opioids (e.g., hydrocodone, oxycodone, other opioid analgesics, excluding methadone or buprenorphine). Compared to non-abstinent individuals, those in both categories of opioid abstinence had lower problem severity in health and social functioning at the final follow-up. Logistic regression results indicated that cocaine users and injection drug users were less likely to achieve 5-year heroin abstinence, whereas Hispanics (vs. whites) and those treated in clinics on the West Coast (vs. East) were less likely to achieve 5-year abstinence from heroin and other opioids. For both abstinence category groups, abstinence was positively associated with older age at first opioid use, lower impulsivity, longer duration of treatment for OUD, and greater social support. Reducing cocaine use and injection drug use and increasing social support and retention in treatment may help maintain long-term abstinence from opioids among individuals treated with agonist pharmacotherapy.

Esophageal carcinoma (EC) is a serious malignancy, and its epidemiologic etiology is not fully explained. We performed this review to investigate the association between teeth loss and teeth brushing and the risk of EC. A systematic search was conducted to identify all relevant studies. The Q test and I2 statistic were used to examine between-study heterogeneity. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were considered by fixed or random effects models. Furthermore, we conducted subgroup analyses based on study design, the studies’ geographic regions and case type of origin. Modified Egger linear regression test was used to estimate publication bias. Ten articles were included. Pooled analyses indicated that teeth loss was associated with an increased risk of EC for Asians (OR, 1.52; 95% CI: 1.30, 1.78), and high frequency of teeth brushing was associated with a lower incidence of EC (OR, 0.62; 95%CI: 0.43, 0.89). Subgroup analyses showed consistent results and no publication bias existed. Teeth loss and teeth brushing play potential roles in the progressing of EC. People should take care of their oral health in daily life. And large well-designed researches are needed to fully describe the association between teeth health and EC risk.

AimsTo compare long‐term criminal justice outcomes among opioid‐dependent individuals randomized to receive buprenorphine or methadone.Design, setting and participantsA 5‐year follow‐up was conducted in 2011–14 of 303 opioid‐dependent participants entering three opioid treatment programs in California, USA in 2006–09 and randomized to receive either buprenorphine/naloxone or methadone.Intervention and comparatorParticipants received buprenorphine/naloxone (BUP; n = 179) or methadone (MET; n = 124) for 24 weeks and then were tapered off their treatment over ≤ 8 weeks or referred for ongoing clinical treatment. Midway through the study, the randomization scheme was switched from 1 : 1 BUP : MET to 2 : 1 because of higher dropout in the BUP arm.MeasurementsStudy outcomes included arrests and self‐reported incarceration. Predictors included randomization condition (buprenorphine versus methadone), age, gender, race/ethnicity, use of cocaine, drug injection in the 30 days prior to baseline and study site. Treatment status (buprenorphine, methadone, none) during follow‐up was included as a time‐varying covariate.FindingsThere was no significant difference by randomization condition in the proportion arrested (buprenorphine: 55.3%, methadone: 54.0%) or incarcerated (40.9%, 47.3%) during follow‐up. Among methadone‐randomized individuals, arrest was less likely with methadone treatment (0.50, 0.35–0.72) during follow‐up (relative to no treatment) and switching to buprenorphine had a lower likelihood of arrest than those receiving no treatment (0.39, 0.18–0.87). Among buprenorphine‐randomized individuals, arrest was less likely with receipt of buprenorphine (0.49, 0.33–0.75) during follow‐up and switching to methadone had a similar likelihood of arrest as methadone‐randomized individuals receiving no treatment. Likelihood of arrest was also negatively associated with older age (0.98, 0.96–1.00); it was positively associated with Hispanic ethnicity (1.63, 1.04–2.56), cocaine use (2.00, 1.33–3.03), injection drug use (2.19, 1.26–3.83), and study site.ConclusionsIn a US sample of people treated for opioid use disorder, continued treatment with either buprenorphine or methadone was associated with a reduction in arrests relative to no treatment. Cocaine use, injection drug use, Hispanic ethnicity and younger age were associated with higher likelihood of arrest.

OBJECTIVE: Prescription Drug Monitoring Programs (PDMPs) are intended to help reduce prescription drug misuse and opioid overdose, yet little is known about the longitudinal patterns of opioid prescribing that may be associated with mortality. This study investigated longitudinal opioid prescribing patterns among patients with opioid use disorder (OUD) and without OUD in relation to mortality using PDMP data. METHODS: Growth modeling was used to examine opioid prescription data from the California PDMP over a 4-year period prior to death or a comparable period ending in 2014 for those remaining from a sample of 7,728 patients (2,576 with OUD, and 5,152 matched non-OUD controls) treated in a large healthcare system. RESULTS: Compared to controls, individuals with OUD (alive and deceased) had received significantly more opioid prescriptions, greater number of days’ supply, and steeper increases of opioid dosages over time. For morphine equivalents (ME, in grams), the interaction of OUD and mortality was significant at both intercept (β=10.4, SE=4.4, p<.05) and slope (β=6.0, SE=1.1, p<.001); deceased OUD patients demonstrated the sharpest increase (i.e., an average yearly increment of 7.84 grams over alive patients without OUD) and ended with the highest level of opioids prescribed before they died (i.e., 20.2 grams higher). Older age, public health insurance, cancer, and chronic pain were associated with higher number and dose of opioid prescriptions. CONCLUSIONS: Besides the amount of prescriptions, clinicians must be alert to patterns of opioid prescription such as escalating dosage as critical warning signals for heightened mortality risks, particularly among patients with OUD.

The pandemic of coronavirus disease 2019 (COVID-19) has posed serious challenges. It is vitally important to further clarify the epidemiological characteristics of the COVID-19 outbreak for future study and prevention and control measures. Epidemiological characteristics and spatial−temporal analysis were performed based on COVID-19 cases from 21 January 2020 to 1 March 2020 in Shandong Province, and close contacts were traced to construct transmission chains. A total of 758 laboratory-confirmed cases were reported in Shandong. The sex ratio was 1.27: 1 (M: F) and the median age was 42 (interquartile range: 32–55). The high-risk clusters were identified in the central, eastern and southern regions of Shandong from 25 January 2020 to 10 February 2020. We rebuilt 54 transmission chains involving 209 cases, of which 52.2% were family clusters, and three widespread infection chains were elaborated, occurring in Jining, Zaozhuang and Liaocheng, respectively. The geographical and temporal disparity may alert public health agencies to implement specific measures in regions with different risk, and should attach importance on how to avoid household and community transmission.