Prescription Opioid Use: An Assessment of Social Factors and Birth Cohort Trends

The relentless rise in drug overdose deaths in the United States underscores the urgent need to broaden the scope of the current response and prioritize approaches that address the social and structural drivers of opioid-related outcomes. As foundational work to advance our understanding of the dynamics underlying the opioid crisis, this dissertation had two aims: (1) identify upstream individual- and contextual-level social factors associated with prescription opioid use, with factors encompassing five domains (economic stability, social/community context, health care access/quality, education access/quality, neighborhood/built environment); (2) quantify the separate influences of age, period, and cohort on longitudinal trends in prescription opioid use. Leveraging available data from two large longitudinal cohort studies, the National Longitudinal Study of Adolescent to Adult Health (n=14,800) and the Johnston County Osteoarthritis Project (n=785), multivariable logistic regression models were used to estimate associations between social exposures and prescription opioid use among young adults (Add Health) and middle-aged to older adults (JoCoOA) across multiple study timepoints during 2001-2019. Lower individual-level educational attainment was associated with increased odds of prescription opioid use for all timepoints assessed. Poorer social support across age groups and unemployment among middle-aged to older adults were also associated with increased opioid use. To characterize longitudinal trends in prescription opioid use, an age-period-cohort analysis was conducted using National Health and Nutrition Examination Survey data (1999-2018; n=63,500). Prescription opioid use increased across the lifespan, with steeper increases from young- to mid-adulthood. Period-related variation was consistent with nationwide shifts in opioid prescribing. There was no evidence of systematic cohort effects, suggesting that prescription opioid use during 1999-2018 was largely driven by age and period influences.The circumstances contributing to prescription opioid use throughout the lifespan and during the overdose crisis are complex, highlighting the need for continued efforts to monitor opioid use in the context of the ever-evolving overdose crisis. This work identified educational attainment and social support as key social factors related to prescription opioid use that require our focus for further in-depth investigation and exploration of intervention approaches, such as those aimed at promoting education access and fostering social connection, which altogether may influence opioid-related outcomes.Doctor of Philosoph

Sociodemographic and Clinical Predictors of Prescription Opioid Use in a Longitudinal Community-Based Cohort Study of Middle-Aged and Older Adults

Objectives: Identifying factors associated with opioid use in middle-aged and older adults is a fundamental step in the mitigation of potentially unnecessary opioid consumption and opioid-related harms. Methods: Using longitudinal data on a community-based cohort of adults aged 50-90 years residing in Johnston County, North Carolina, we examined sociodemographic and clinical factors in non-opioid users (n = 786) at baseline (2006-2010) as predictors of opioid use at follow-up (2013-2015). Variables included age, sex, race, obesity, educational attainment, employment status, household poverty rate, marital status, depressive symptoms, social support, pain catastrophizing, pain sensitivity, insurance status, polypharmacy, and smoking status. Results: At follow-up, 13% of participants were using prescription opioids. In the multivariable model, high pain catastrophizing (adjusted odds ratio; 95% confidence interval = 2.14; 1.33-3.46), polypharmacy (2.08; 1.23-3.53), and history of depressive symptoms (2.00; 1.19-3.38) were independent markers of opioid use. Discussion: Findings support the assessment of these modifiable factors during clinical encounters in patients ≥ 50 years old with chronic pain

Sociodemographic and Clinical Predictors of Prescription Opioid Use in a Longitudinal Community-Based Cohort Study of Middle-Aged and Older Adults

Background: Despite declining opioid prescribing rates in the United States, the annual prevalence of prescription opioid use in adults ≥50 years old is estimated to be 40%, higher than that of younger adults (ages 18-29 years, 36%). As the American population ages, understanding factors that contribute to overall opioid use is a necessary first step in the determination and mitigation of inappropriate prescribing and opioid-related harms. Objective: Assess predictors of prescription opioid use in an adult population with a high prevalence of chronic pain. Methods: Data were from a community-based cohort of White and African American adults aged 50-90 years residing in predominantly rural Johnston County, North Carolina. Univariable and multivariable logistic regression models were used to evaluate sociodemographic and clinical factors in non-opioid users (n=795) at baseline (2006-2010) as predictors of opioid use at follow-up (2013-2015). Variables included age, sex, race, obesity (BMI≥30kg/m2), polypharmacy (5+ medications), educational attainment (<12, ≥12 years), employment (unemployed, employed/retired), insurance (uninsured, public, private), Census block group household poverty rate (<12%, 12–24%, ≥25%), depressive symptoms (Center for Epidemiologic Studies Depression Scale ≥16 or depression diagnosis), perceived social support (moderate/poor [<19], strong [≥19]; Strong Ties Measure of Social Support, range 0-20), pain sensitivity (sensitive [<4kg], normal [≥4kg] pressure pain threshold), and pain catastrophizing (high [≥15], moderate/low [<15]; Pain Catastrophizing Helplessness Subscale, range 0-25). Results: At follow-up, 13% (n=100) of participants were using prescription opioids. In univariable models, younger age, female sex, obesity, polypharmacy, unemployment, public (vs. private) health insurance, higher poverty rate, depressive symptoms, poorer perceived social support, pain catastrophizing, and elevated pain sensitivity were independently associated (p<0.05) with opioid use. In the multivariable model, younger age (60 vs. 70 years; adjusted odds ratio, 95% confidence interval=2.52, 1.08−5.88), polypharmacy (2.16, 1.24−3.77), high pain catastrophizing (2.17, 1.33−3.56), and depressive symptoms (2.00, 1.17−3.43) remained significant independent predictors. Conclusion: The simultaneous assessment of a breadth of clinical and sociodemographic factors identified polypharmacy, pain catastrophizing, and depressive symptoms as modifiable predictors of prescription opioid use. These findings support the incorporation of pharmacological review and behavioral approaches into chronic pain management strategies. Further research is warranted to track changes in these factors as prescription opioid use declines nationwide

Sociodemographic and Clinical Predictors of Prescription Opioid Use in a Longitudinal Community-Based Cohort Study of Middle-Aged and Older Adults

Background: Despite declining opioid prescribing rates in the United States, the annual prevalence of prescription opioid use in adults ≥50 years old is estimated to be 40%, higher than that of younger adults (ages 18-29 years, 36%). As the American population ages, understanding factors that contribute to overall opioid use is a necessary first step in the determination and mitigation of inappropriate prescribing and opioid-related harms. Objective: Assess predictors of prescription opioid use in an adult population with a high prevalence of chronic pain. Methods: Data were from a community-based cohort of White and African American adults aged 50-90 years residing in predominantly rural Johnston County, North Carolina. Univariable and multivariable logistic regression models were used to evaluate sociodemographic and clinical factors in non-opioid users (n=795) at baseline (2006-2010) as predictors of opioid use at follow-up (2013-2015). Variables included age, sex, race, obesity (BMI≥30kg/m2), polypharmacy (5+ medications), educational attainment (<12, ≥12 years), employment (unemployed, employed/retired), insurance (uninsured, public, private), Census block group household poverty rate (<12%, 12–24%, ≥25%), depressive symptoms (Center for Epidemiologic Studies Depression Scale ≥16 or depression diagnosis), perceived social support (moderate/poor [<19], strong [≥19]; Strong Ties Measure of Social Support, range 0-20), pain sensitivity (sensitive [<4kg], normal [≥4kg] pressure pain threshold), and pain catastrophizing (high [≥15], moderate/low [<15]; Pain Catastrophizing Helplessness Subscale, range 0-25). Results: At follow-up, 13% (n=100) of participants were using prescription opioids. In univariable models, younger age, female sex, obesity, polypharmacy, unemployment, public (vs. private) health insurance, higher poverty rate, depressive symptoms, poorer perceived social support, pain catastrophizing, and elevated pain sensitivity were independently associated (p<0.05) with opioid use. In the multivariable model, younger age (60 vs. 70 years; adjusted odds ratio, 95% confidence interval=2.52, 1.08−5.88), polypharmacy (2.16, 1.24−3.77), high pain catastrophizing (2.17, 1.33−3.56), and depressive symptoms (2.00, 1.17−3.43) remained significant independent predictors. Conclusion: The simultaneous assessment of a breadth of clinical and sociodemographic factors identified polypharmacy, pain catastrophizing, and depressive symptoms as modifiable predictors of prescription opioid use. These findings support the incorporation of pharmacological review and behavioral approaches into chronic pain management strategies. Further research is warranted to track changes in these factors as prescription opioid use declines nationwide

Race, insurance type, and stage of presentation among lung cancer patients

The purpose of this study was to determine whether African-American lung cancer patients are diagnosed at a later stage than white patients, regardless of insurance type. The relationship between race and stage at diagnosis by insurance type was assessed using a Poisson regression model, with relative risk as the measure of association. The setting of the study was a large tertiary care cancer center located in the southeastern United States. Patients who were diagnosed with lung cancer between 2001 and 2010 were included in the study. A total of 717 (31%) African-American and 1,634 (69%) white lung cancer patients were treated at our facility during the study period. Adjusting for age, sex, and smoking-related histology, African-American patients were diagnosed at a statistically significant later stage (III/IV versus I/II) than whites for all insurance types, with the exception of Medicaid. Our results suggest that equivalent insurance coverage may not ensure equal presentation of stage between African-American and white lung cancer patients. Future research is needed to determine whether other factors such as treatment delays, suboptimal preventive care, inappropriate specialist referral, community segregation, and a lack of patient trust in health care providers may explain the continuing racial disparities observed in the current study

Racial and ethnic differences and COVID-19 pandemic-related changes in drug overdose deaths in North Carolina

Purpose To examine racial/ethnic differences and COVID-19 pandemic-related changes in key characteristics of drug overdose deaths in North Carolina. Methods We used North Carolina State Unintentional Drug Overdose Reporting System (NC-SUDORS) data to describe specific drug-involvement, bystander presence, and naloxone administration for drug overdose deaths by race/ethnicity during pre-COVID-19 (May 2019–February 2020) and COVID-19 periods (March 2020–December 2020). Results For all racial/ethnic groups, drug overdose death rates and the percentage with fentanyl and alcohol involvement increased from the pre-COVID-19 to COVID-19 period, with fentanyl involvement highest among American Indian/Alaska Native (82.2%) and Hispanic (81.4%) individuals and alcohol involvement highest among Hispanic individuals (41.2%) during the COVID-19 period. Cocaine involvement remained high among Black non-Hispanic individuals (60.2%) and increased among American Indian/Alaska Native individuals (50.6%). There was an increase in the percentage of deaths with a bystander present from the pre-COVID-19 to COVID-19 period for all racial/ethnic groups, with more than half having a bystander present during the COVID-19 period. There was a decrease in the percentage with naloxone administered for most racial/ethnic groups, with the lowest percentage among Black non-Hispanic individuals (22.7%). Conclusions Efforts to address increasing inequities in drug overdose deaths, including expanded community naloxone access, are needed

Viral dynamics of acute SARS-CoV-2 infection and applications to diagnostic and public health strategies.

SARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening. We used prospective longitudinal quantitative reverse transcription PCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019-2020 National Basketball Association season. For 46 individuals with acute infections, we inferred the peak viral concentration and the duration of the viral proliferation and clearance phases. According to our mathematical model, we found that viral RNA concentrations peaked an average of 3.3 days (95% credible interval [CI] 2.5, 4.2) after first possible detectability at a cycle threshold value of 22.3 (95% CI 20.5, 23.9). The viral clearance phase lasted longer for symptomatic individuals (10.9 days [95% CI 7.9, 14.4]) than for asymptomatic individuals (7.8 days [95% CI 6.1, 9.7]). A second test within 2 days after an initial positive PCR test substantially improves certainty about a patient's infection stage. The effective sensitivity of a test intended to identify infectious individuals declines substantially with test turnaround time. These findings indicate that SARS-CoV-2 viral concentrations peak rapidly regardless of symptoms. Sequential tests can help reveal a patient's progress through infection stages. Frequent, rapid-turnaround testing is needed to effectively screen individuals before they become infectious

The Burden of Mental Disorders in the Eastern Mediterranean Region, 1990-2013

Charara R, Forouzanfar M, Naghavi M, et al. The Burden of Mental Disorders in the Eastern Mediterranean Region, 1990-2013. PLOS ONE. 2017;12(1): e0169575.The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health services and to address the stigma of mental illness. Moreover, our results showing the accelerating burden of mental health are alarming as the region is seeing an increased level of instability. Indeed, mental health problems, if not properly addressed, will lead to an increased burden of diseases in the region

Burden of musculoskeletal disorders in the Eastern Mediterranean Region, 1990–2013: findings from the Global Burden of Disease Study 2013

Moradi-Lakeh M, Forouzanfar MH, Vollset SE, et al. Burden of musculoskeletal disorders in the Eastern Mediterranean Region, 1990–2013: findings from the Global Burden of Disease Study 2013. Annals of the Rheumatic Diseases. 2017;76(8):annrheumdis-2016-210146

Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS: We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS: Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, an