Explore the vast range of titles available.

Background College students are a key population for opioid use, misuse, and subsequent exposure to overdose events. However, their knowledge and attitudes in response to opioid overdose warrant further study. To assess this gap, we surveyed graduate and undergraduate students about their opioid overdose knowledge, attitudes, self-reported competence, readiness to act, and concerns or barriers to intervention. Methods We conducted a cross-sectional survey of 252 undergraduate and graduate students at a large public university in the southern United States. Opioid overdose knowledge was assessed using the 45-item Opioid Overdose Knowledge Scale (OOKS), and attitudes toward overdose response—including perceived competence, readiness to act, and concerns—were measured using the Opioid Overdose Attitudes Scale (OOAS). Independent-samples t tests were used to compare knowledge and attitude scores across selected groups relevant to overdose education and naloxone training, including pre-health status and prior overdose prevention training. Open-ended responses regarding interest in naloxone training were analyzed using thematic analysis. Results Participants demonstrated moderate overall overdose knowledge (mean OOKS score: 28.2 ± 8.6), with stronger performance in naloxone-related domains and persistent gaps in recognizing overdose risk factors and signs. Students with prior overdose prevention or naloxone training consistently reported higher knowledge, perceived competence, and readiness to intervene compared with untrained peers. Despite limited prior training (9.9%), nearly two-thirds of participants expressed interest in receiving naloxone training. Thematic analysis identified “Preparedness,” “Helping Others,” and “Confidence” as motivators and “Low Perceived Risk,” “Time Constraints,” and “Stigma” as barriers. Conclusion Although students exhibit moderate overdose knowledge, targeted naloxone training is essential for enhancing their competence and readiness to address opioid overdose. Tailored campus programs that address identified barriers and leverage motivational themes may strengthen emergency response and reduce overdose fatality.

Study Objectives: Screening for early detection of sleep-disordered breathing in hospitalized patients has been shown to reduce readmission rates. However, postdischarge polysomnography for confirmation of diagnosis is required. We analyzed factors for “no-shows” using geospatial techniques. Methods: Data were obtained between September 2019 and September 2023. The outcome for the study was patients’ no-show rate (nonadherent for polysomnography) after hospital discharge. Predictors included the patient’s age, sex, body mass index, health literacy, Distressed Communities Index score, and distance to a sleep center for the patient’s zip code of residence. Logistic regression was applied to estimate odds of patients’ adherence at the patient level using a geospatial mapping technique. Geographically weighted logistic regression was applied to estimate the odds of a zip code’s including adherent patients. Results: Of the 1,318 hospitalized patients established as high-risk for sleep-disordered breathing and referred for an overnight sleep study who were able to be geocoded, 228 were adherent and 1,130 were nonadherent. In nonspatial regression analyses, health literacy (adjusted odds ratio = 1.06; 95% confidence interval = 1.03, 1.09), age (adjusted odds ratio = 0.99; 95% confidence interval = 0.98, 0.99), and drive time (adjusted odds ratio = 0.95; 95% confidence interval = 0.92, 0.97) were identified as statistically significant predictors of patients’ adherence. Spatial regression analyses identified areas that had high and low predictive probability of patients’ adherence, as well as which community-level factors were co-occurring in those areas. Conclusions: The findings suggest that both patient-level factors and the community where patients live may impact no-show rates. Health literacy was identified as a key modifiable predictor at the patient level. At the community level, we found that predicted probability of patient adherence varied throughout the state. Efforts should focus on enhancing patients’ education at the individual level and understanding geographical factors to improve adherence. Citation: Sharma S, Stansbury R, Rojas E, et al. Factors impacting sleep center no-show rates after hospital discharge using geospatial coding in Appalachia. J Clin Sleep Med. 2025;21(4):667–674.

Background Peripheral artery disease (PAD) is a common circulatory disorder associated with increased hospitalizations and significant health care-related expenditures. Among patients with PAD, insurance status is an important determinant of health care utilization, treatment of disease, and treatment outcomes. However, little is known about PAD-costs differences across different insurance providers. In this study we examined possible disparities in length of stay and total charge of inpatient hospitalizations among patients with PAD by insurance type. Methods We conducted a cross-sectional analysis of length of stay and total charge by insurance provider for all hospitalizations for individuals with PAD in South Carolina (2010–2018). Cross-classified multilevel modeling was applied to account for the non-nested hierarchical structure of the data, with county and hospital included as random effects. Analyses were adjusted for patient age, race/ethnicity, county, year of admission, admission type, all-patient refined diagnostic groups, and Charlson comorbidity index. Results Among 385,018 hospitalizations for individuals with PAD in South Carolina, the median length of stay was 4 days (IQR: 5) and the median total charge of hospitalization was $43,232 (IQR: $52,405). Length of stay and total charge varied significantly by insurance provider. Medicare patients had increased length of stay (IRR = 1.08, 95 CI%: 1.07, 1.09) and higher total charges (β: 0.012, 95% CI: 0.007, 0.178) than patients with private insurance. Medicaid patients also had increased length of stay (IRR = 1.26, 95% CI: 1.24,1.28) but had lower total charges (β: -0.022, 95% CI: -0.003. -0.015) than patients with private insurance. Conclusions Insurance status was associated with inpatient length of stay and total charges in patients with PAD. It is essential that Medicare and Medicaid individuals with PAD receive proper management and care of their PAD, particularly in the primary care settings, to prevent hospitalizations and reduce the excess burden on these patients.

Socioeconomic factors have been shown to be associated with amputation in peripheral artery disease (PAD); however, analyses have normally focused on insurance status, race, or median income. We sought to determine whether community-level socioeconomic distress was associated with major amputation and if that association differed by race. Community-level socioeconomic distress was measured using the distressed communities index (DCI). The DCI is a zip code level compositive socioeconomic score (0-100) that accounts for unemployment, education level, poverty rate, median income, business growth, and housing vacancies. A distressed community was defined as a zip code with DCI of 40 or greater. We calculated one-year risk of major amputation by DCI score for individuals with peripheral artery disease in South Carolina, 2012-2017. Treating death as competing event, we reported Fine and Gray subdistribution hazards ratios (sdHR), adjusted for patient demographic and clinical comorbidities associated with amputation. Further analyses were completed to identify potential differences in outcomes within strata of race and DCI. Among 82,848 individuals with peripheral artery disease, the one-year incidence of amputation was 3.5% (95% CI: 3.3%, 3.6%) and was significantly greater in distressed communities than non-distressed communities (3.9%; 95% CI: 3.8%, 4.1% vs. 2.4%; 95% CI: 2.2%, 2.6%). After controlling for death and adjusting for covariates, we found an increased hazard of amputation among individuals in a distressed community (sdHR: 1.25; 95% CI: 1.14, 1.37), which persisted across racial strata. However, regardless of DCI score, Black individuals had the highest incidence of amputation. Socioeconomic status is independently predictive of limb amputation after controlling for demographic characteristics and clinical comorbidities. Race continues to be an important risk factor, with Black individuals having higher incidence of amputation, even in non-distressed communities, than White individuals had in distressed communities.

Rural underserved areas facing health disparities have unequal access to health resources. By the third and fourth waves of SARS-CoV-2 infections in the United States, COVID-19 testing had reduced, with more reliance on home testing, and those seeking testing were mostly symptomatic. This study identifies factors associated with COVID-19 testing among individuals who were symptomatic versus asymptomatic seen at a Rapid Acceleration of Diagnostics for Underserved Populations phase 2 (RADx-UP2) testing site in West Virginia. Demographic, clinical, and behavioral factors were collected via survey from tested individuals. Logistic regression was used to identify factors associated with the presence of individuals who were symptomatic seen at testing sites. Global tests for spatial autocorrelation were conducted to examine clustering in the proportion of symptomatic to total individuals tested by zip code. Bivariate maps were created to display geographic distributions between higher proportions of tested individuals who were symptomatic and social determinants of health. Among predictors, the presence of a physical (adjusted odds ratio [aOR] 1.85, 95% CI 1.3-2.65) or mental (aOR 1.53, 95% CI 0.96-2.48) comorbid condition, challenges related to a place to stay/live (aOR 307.13, 95% CI 1.46-10,6372), no community socioeconomic distress (aOR 0.99, 95% CI 0.98-1.00), no challenges in getting needed medicine (aOR 0.01, 95% CI 0.00-0.82) or transportation (aOR 0.23, 95% CI 0.05-0.64), an interaction between community socioeconomic distress and not getting needed medicine (aOR 1.06, 95% CI 1.00-1.13), and having no community socioeconomic distress while not facing challenges related to a place to stay/live (aOR 0.93, 95% CI 0.87-0.99) were statistically associated with an individual being symptomatic at the first test visit. This study addresses critical limitations to the current COVID-19 testing literature, which almost exclusively uses population-level disease screening data to inform public health responses.

This study examined engagement in five health behaviors among pregnant women in the USA. Pregnant women who participated in the National Health and Nutrition Examination Survey 2007-2014 were included in this study. Five health behaviors were examined: adequate fruit and vegetable consumption, prenatal multivitamin use, physical activity, sleep and smoking. Multivariable regressions were used to estimate the odds ratio and 95% confidence interval of characteristics associated with health behaviors. Among 248 pregnant women, only 10.2% engaged in all five health behaviors and 35.4% consumed adequate fruits and vegetables. For adequate fruit and vegetable consumption, Hispanic and women of 'other' race were more likely to meet the recommendation compared to non-Hispanic white (P = 0.01 and P = 0.03, respectively); high school graduates were less likely to meet the recommendation compared to those with at least some college education or more (P = 0.04). Adequate fruit and vegetable consumption among pregnant women was poor and differed by race/ethnicity and education status. Because of the cross-sectional design, we cannot examine engagement in health behaviors continuously throughout pregnancy. Future research with longitudinal data over the course of pregnancy is needed to confirm these results.

Background Attention-deficit hyperactivity disorder is a common disorder that affects both children and adults. However, for adults, little is known about ADHD-attributable medical expenditures. Objective To estimate the medical expenditures associated with ADHD, stratified by age, in the US adult population. Design Using a two-part model, we analyzed data from Medical Expenditure Panel Survey for 2015 to 2019. The first part of the model predicts the probability that individuals incurred any medical costs during the calendar year using a logit model. The second part of the model estimates the medical expenditures for individuals who incurred any medical expenses in the calendar year using a generalized linear model. Covariates included age, sex, race/ethnicity, geographic region, Charlson comorbidity index, insurance, asthma, anxiety, and mood disorders. Participants Adults (18 +) who participated in the Medical Expenditure Panel Survey from 2015 to 2019 ( N  = 83,776). Main Measures Overall and service specific direct ADHD-attributable medical expenditures. Key Results A total of 1206 participants (1.44%) were classified as having ADHD. The estimated incremental costs of ADHD in adults were $2591.06 per person, amounting to $8.29 billion nationally. Significant adjusted incremental costs were prescription medication ($1347.06; 95% CI: $990.69–$1625.93), which accounted for the largest portion of total costs, and office-based visits ($724.86; 95% CI: $177.75–$1528.62). The adjusted incremental costs for outpatient visits, inpatient visits, emergency room visits, and home health visits were not significantly different. Among older adults (31 +), the incremental cost of ADHD was $2623.48, while in young adults (18–30), the incremental cost was $1856.66. Conclusions The average medical expenditures for adults with ADHD in the US were substantially higher than those without ADHD and the incremental costs were higher in older adults (31 +) than younger adults (18–30). Future research is needed to understand the increasing trend in ADHD attributable cost.

Readmissions constitute a major health care burden among peripheral artery disease (PAD) patients. This study aimed to 1) estimate the zip code tabulation area (ZCTA)-level prevalence of readmission among PAD patients and characterize the effect of covariates on readmissions; and (2) identify hotspots of PAD based on estimated prevalence of readmission. Thirty-day readmissions among PAD patients were identified from the South Carolina Revenue and Fiscal Affairs Office All Payers Database (2010–2018). Bayesian spatial hierarchical modeling was conducted to identify areas of high risk, while controlling for confounders. We mapped the estimated readmission rates and identified hotspots using local Getis Ord (G*) statistics. Of the 232,731 individuals admitted to a hospital or outpatient surgery facility with PAD diagnosis, 30,366 (13.1%) experienced an unplanned readmission to a hospital within 30 days. Fitted readmission rates ranged from 35.3 per 1000 patients to 370.7 per 1000 patients and the risk of having a readmission was significantly associated with the percentage of patients who are 65 and older (0.992, 95%CI: 0.985–0.999), have Medicare insurance (1.013, 1.005–1.020), and have hypertension (1.014, 1.005–1.023). Geographic analysis found significant variation in readmission rates across the state and identified priority areas for targeted interventions to reduce readmissions.

ObjectivesGroup prenatal care (GPC), an alternative to individual prenatal care (IPC), is becoming more prevalent. This study aimed to describe the attendance and reasons of low attendance among pregnant women who were randomly assigned to receive GPC or IPC and explore the maternal characteristics associated with low-attendance.MethodsThis study was a descriptive study among Medically low risk pregnant women (N = 992) who were enrolled in an ongoing prospective study. Women were randomly assigned to receive CenteringPregnany GPC (N = 498) or IPC (N = 994) in a single clinical site The attendance frequency and reason for low-attendance (i.e. ≤ 5/10 sessions in GPC or ≤ 5 visits in IPC) were described separately in GPC and IPC. Multivariable logistic regressions were performed to explore the associations between maternal characteristics and low-attendance.ResultsOn average, women in GPC attended 5.32 (3.50) sessions, with only 6.67% attending all 10 sessions. Low-attendance rate was 34.25% in GPC and 10.09% in IPC. The primary reasons for low-attendance were scheduling barriers (23.19%) and not liking GPC (16.43%) in GPC but leaving the practice (34.04%) in IPC. In multivariable analysis, lower perceived family support (P = 0.01) was positively associated with low-attendance in GPC, while smoking in early pregnancy was negatively associated low-attendance (P = 0.02) in IPC.Conclusions for PracticeScheduling challenges and preference for non-group settings were the top reasons for low-attendance in GPC. Changes may need to be made to the current GPC model in order to add flexibility to accommodate women’s schedules and ensure adequate participation.Trial registrationNCT02640638 Date Registered: 12/20/2015.

In collaboration with state, tribal, local, and territorial health departments, CDC established the U.S. Zika Pregnancy Registry (USZPR) in early 2016 to monitor pregnant women with laboratory evidence of possible recent Zika virus infection and their infants. This report includes an analysis of completed pregnancies (which include live births and pregnancy losses, regardless of gestational age) in the 50 U.S. states and the District of Columbia (DC) with laboratory evidence of possible recent Zika virus infection reported to the USZPR from January 15 to December 27, 2016. Birth defects potentially associated with Zika virus infection during pregnancy include brain abnormalities and/or microcephaly, eye abnormalities, other consequences of central nervous system dysfunction, and neural tube defects and other early brain malformations. During the analysis period, 1,297 pregnant women in 44 states were reported to the USZPR. Zika virus-associated birth defects were reported for 51 (5%) of the 972 fetuses/infants from completed pregnancies with laboratory evidence of possible recent Zika virus infection (95% confidence interval [CI] = 4%-7%); the proportion was higher when restricted to pregnancies with laboratory-confirmed Zika virus infection (24/250 completed pregnancies [10%, 95% CI = 7%-14%]). Birth defects were reported in 15% (95% CI = 8%-26%) of fetuses/infants of completed pregnancies with confirmed Zika virus infection in the first trimester. Among 895 liveborn infants from pregnancies with possible recent Zika virus infection, postnatal neuroimaging was reported for 221 (25%), and Zika virus testing of at least one infant specimen was reported for 585 (65%). These findings highlight why pregnant women should avoid Zika virus exposure. Because the full clinical spectrum of congenital Zika virus infection is not yet known, all infants born to women with laboratory evidence of possible recent Zika virus infection during pregnancy should receive postnatal neuroimaging and Zika virus testing in addition to a comprehensive newborn physical exam and hearing screen. Identification and follow-up care of infants born to women with laboratory evidence of possible recent Zika virus infection during pregnancy and infants with possible congenital Zika virus infection can ensure that appropriate clinical services are available.