Vaping Transitions and Incident Depressive Symptoms among Young Adults: A Marginal Structural Model Analysis.

The extent to which vaping influences depression is unclear, but could be estimated through application of novel epidemiologic methods. Among a prospective cohort of young adults from California who screened negative for depression, we estimated repeated measures marginal structural models to examine the association of four vaping transitions from time T to T+1 (persistent use, discontinuation, initiation, persistent nonuse) with risk of clinically significant depressive symptoms at T+1, simultaneously across three ~1.5 year time-intervals between 2017-2021. Stabilized inverse probability of treatment and censoring weights adjusted for time-dependent confounders and selection bias. Among n=3,496 observations (1,806 participants, mean pooled baseline age=19.5), 8.1% reported persistent vaping from T to T+1, 6.2% reported discontinuation (i.e., use at T and no use at T+1), 6.5% initiated e-cigarettes (i.e., no use at T and use at T+1), and 79.2% reported persistent nonuse at both time-points. Compared to persistent vaping at two waves, persistent nonuse (RR=0.76, 95%CI:0.62-0.93) and discontinuation (RR=0.71, 95%CI:0.52-0.96) were associated with lower risk of depression. Associations were robust to sensitivity analyses, including restricting to tobacco naïve participants and varying temporal assumptions to reduce potential for reverse causation. Young adults who consistently avoid or discontinue vaping may be protected from depressive symptom occurrence.

Metabolic Disease and The Risk of Post-COVID Conditions: A Retrospective Cohort Study.

Objective: To examine the influence of having a baseline metabolic disorder (diabetes, hypertension, and/or obesity) on the risk of developing new clinical sequelae potentially related to SARS-CoV-2 in a large sample of commercially insured adults in the US. Design setting and participants: Deidentified data were collected from the IBM/Watson MarketScan Commercial Claims and Encounters (CCAE) Databases and Medicare Supplemental and Coordination of Benefits (MDCR) Databases from 2019 to 2021. A total of 839,344 adults aged 18 and above with continuous enrollment in the health plan were included in the analyses. Participants were grouped into four categories based on their COVID-19 diagnosis and whether they had at least one of the three common metabolic disorders at baseline (diabetes, obesity, or hypertension). Measures and methods: ICD-10-CM codes were used to determine new symptoms and conditions after the acute phase of SARS-CoV-2 infection, defined as ending 21 days after initial diagnosis date, or index period for those who did not have a COVID-19 diagnosis. Propensity score matching (PSM) was used to create comparable reference groups. Cox proportional hazard models were conducted to estimate hazard ratios and 95% confidence intervals. Results: Among the 772,377 individuals included in the analyses, 36,742 (4.8%) without and 20,912 (2.7%) with a baseline metabolic disorder were diagnosed with COVID-19. On average, COVID-19 patients with baseline metabolic disorders had more 2.4 more baseline comorbidities compared to those without baseline metabolic disorders. Compared to adults with no baseline metabolic condition, the risks of developing new clinical sequelae were highest among COVID-19 patients with a baseline metabolic condition (HRs ranging from 1.51 to 3.33), followed by those who had a baseline metabolic condition but with no COVID-19 infection (HRs ranging from 1.33 to 2.35), and those who had COVID-19 but no baseline metabolic condition (HRs ranging from 1.34 to 2.85). Conclusions: In a large national cohort of commercially insured adults, COVID-19 patients with a baseline metabolic condition had the highest risk of developing new clinical sequelae post-acute infection phase, followed by those who had baseline metabolic condition but no COVID-19 infection and those who had COVID-19 but no baseline metabolic disorder.

Randomized, placebo-controlled, double-blind phase I trial of co-administered pyronaridine and piperaquine in healthy adults of sub-Saharan origin.

Drug resistance to sulfadoxine-pyrimethamine and amodiaquine threatens the efficacy of malaria chemoprevention interventions in children and pregnant women. Combining pyronaridine (PYR) and piperaquine (PQP), both components of approved antimalarial therapies, has the potential to protect vulnerable populations from severe malaria. This randomized, double-blind, placebo-controlled (double-dummy), parallel-group, single site phase I study in healthy adult males or females of Black sub-Saharan African ancestry investigated the safety, tolerability, and pharmacokinetics of PYR + PQP (n = 15), PYR + placebo (n = 8), PQP + placebo (n = 8), and double placebo (n = 6) administered orally once daily for 3 days at the registered dose for the treatment of uncomplicated malaria. All participants completed the study. Forty-five adverse events were reported in 26 participants, most (41/45) were mild/moderate in severity, with no serious adverse events, deaths, or study withdrawals. Adverse events were reported in 66.7% (10/15) of participants administered PYR + PQP, 87.5% (7/8) with PYR + placebo, 50.0% (4/8) with PQP + placebo, and 83.3% (5/6) with placebo. For PYR containing regimens, five of 23 participants had asymptomatic transient increases in alanine and/or aspartate aminotransferase. With PQP containing regimens, four of 23 participants had mild Fridericia-corrected QT interval prolongation. Liver enzyme elevations and prolonged QTc interval were consistent with observations for PYR-artesunate and dihydroartemisinin-PQP, respectively, administered to healthy adults and malaria patients. Increases in PYR and PQP exposures were observed following co-administration versus placebo, with substantial interparticipant variability. The findings suggest that PYR + PQP may have potential in chemoprevention strategies. Further studies are needed in the target populations to assess chemoprotective efficacy and define the benefit-risk profile, with special considerations regarding hepatic and cardiac safety.

Association of cigarette and electronic cigarette use patterns with all-cause mortality: A national cohort study of 145,390 US adults.

OBJECTIVE: While e-cigarette use is associated with adverse cardiopulmonary health effects, the mortality risks associated with e-cigarette use alone and combined with smoking remain unexamined. METHODS: Data between 2014 and 2018 were obtained from the National Health Interview Survey (NHIS), an annual cross-sectional survey of US adults. All-cause mortality and date of death were obtained via linkage of the NHIS to the National Death Index through December 31, 2019. A 6-category composite cigarette (never, former, current) and e-cigarette (current, non-current) exposure variable was created. We examined the association of cigarette and e-cigarette use patterns with all-cause mortality using adjusted Cox models. RESULTS: Among 145,390 participants (79,294 women [51.5%]; 60,560 aged 18-44 [47.4%]), 5220 deaths were observed over a median follow-up of 3.5 years (508,545 total person-years). Dual use of cigarettes and e-cigarettes was associated with higher mortality risk compared with non-current e-cigarette use in combination with never smoking (hazard ratio [HR] 2.44; 95% CI, 1.90-3.13) and had a risk that did not differ from current exclusive smoking (HR, 1.06; 95% CI, 0.83-1.37). Current e-cigarette use in combination with former smoking was associated with a lower mortality risk than current exclusive cigarette smoking (HR 0.64; 95% CI, 0.41-0.99). CONCLUSIONS: The addition of e-cigarette use to smoking does not reduce mortality risk compared with exclusive smoking. However, transitioning completely from cigarettes to e-cigarettes may be associated with mortality risk reduction. Further research is needed to verify these findings in larger cohorts and over longer periods of follow-up.

Excess natural-cause mortality in US counties and its association with reported COVID-19 deaths.

In the United States, estimates of excess deaths attributable to the COVID-19 pandemic have consistently surpassed reported COVID-19 death counts. Excess deaths reported to non-COVID-19 natural causes may represent unrecognized COVID-19 deaths, deaths caused by pandemic health care interruptions, and/or deaths from the pandemic's socioeconomic impacts. The geographic and temporal distribution of these deaths may help to evaluate which explanation is most plausible. We developed a Bayesian hierarchical model to produce monthly estimates of excess natural-cause mortality for US counties over the first 30 mo of the pandemic. From March 2020 through August 2022, 1,194,610 excess natural-cause deaths occurred nationally [90% PI (Posterior Interval): 1,046,000 to 1,340,204]. A total of 162,886 of these excess natural-cause deaths (90% PI: 14,276 to 308,480) were not reported to COVID-19. Overall, 15.8 excess deaths were reported to non-COVID-19 natural causes for every 100 reported COVID-19 deaths. This number was greater in nonmetropolitan counties (36.0 deaths), the West (Rocky Mountain states: 31.6 deaths; Pacific states: 25.5 deaths), and the South (East South Central states: 26.0 deaths; South Atlantic states: 25.0 deaths; West South Central states: 24.2 deaths). In contrast, reported COVID-19 death counts surpassed estimates of excess natural-cause deaths in metropolitan counties in the New England and Middle Atlantic states. Increases in reported COVID-19 deaths correlated temporally with increases in excess deaths reported to non-COVID-19 natural causes in the same and/or prior month. This suggests that many excess deaths reported to non-COVID-19 natural causes during the first 30 mo of the pandemic in the United States were unrecognized COVID-19 deaths.

Disparities in All-Cause Mortality Beyond the Acute Phase of the COVID-19 Pandemic in the US.

This cross-sectional study examines all-cause mortality in the US between March 2018 and May 2023 by sex, race and ethnicity, metropolitan status, and region.

Electronic cigarette use and chest pain in US adults: Evidence from the PATH study.

INTRODUCTION: Electronic cigarettes (e-cigarette) were introduced for smoking cessation/reduction but have also become popular among the youth. Although e-cigarettes contain fewer toxins than combustible cigarettes, their long-term cardiovascular and pulmonary effects remain unknown. We aimed to assess the association between self-reported chest pain and e-cigarette use. METHODS: We analyzed data from the PATH (Population Assessment of Tobacco and Health) study wave 4 (2016-2018) and wave 5 (2018-2019). Based on questionnaires from wave 4, we categorized tobacco use as: 1) non-use, 2) exclusive e-cigarette use, 3) combustible cigarette use, and 4) dual use. Presence of established cardiovascular disease was examined at wave 4, and participants aged >40 years were asked about chest pain during wave 5. We used binary logistic regression models to determine the association between tobacco exposures and self-reported chest pain. RESULTS: We evaluated a total of 11254 adults. The rates of chest pain were 1518 out of 7055 non-users, 49 from 208 exclusive e-cigarette users, 1192 from 3722 combustible cigarette users, and 99 out of 269 dual users. In the multivariable models adjusted for relevant covariates, combustible cigarette users (adjusted odds ratio, AOR=1.77; 95% CI: 1.56-2.01) and dual users (AOR=2.22; 95% CI: 1.61-3.05) had higher odds of reporting ever having chest pain, as well as having chest pain in the past 30 days. Conversely, exclusive e-cigarette users had similar odds of reporting chest pain compared to non-users (AOR=1.03; 95% CI: 0.69-1.54) and lower odds than combustible and dual users. In sensitivity analyses, categorizing individuals based on their reported history of cardiovascular disease, overall findings were similar. CONCLUSIONS: Exclusive e-cigarette use is associated with a lower rate of chest pain compared to combustible cigarette use and dual use.

Gaps in the type 2 diabetes care cascade: a national perspective using South Africa's National Health Laboratory Service (NHLS) database.

BACKGROUND: Research out of South Africa estimates the total unmet need for care for those with type 2 diabetes mellitus (diabetes) at 80%. We evaluated the care cascade using South Africa's National Health Laboratory Service (NHLS) database and assessed if HIV infection impacts progression through its stages. METHODS: The cohort includes patients from government facilities with their first glycated hemoglobin A1c (HbA1c) or plasma glucose (fasting (FPG); random (RPG)) measured between January 2012 to March 2015 in the NHLS. Lab-diagnosed diabetes was defined as HbA1c ≥ 6.5%, FPG ≥ 7.0mmol/l, or RPG ≥ 11.1mmol/l. Cascade stages post diagnosis were retention-in-care and glycaemic control (defined as an HbA1c < 7.0% or FPG < 8.0mmol/l or RPG < 10.0mmol/l) over 24-months. We estimated gaps at each stage nationally and by people living with HIV (PLWH) and without (PLWOH). RESULTS: Of the 373,889 patients tested for diabetes, 43.2% had an HbA1c or blood glucose measure indicating a diabetes diagnosis. Amongst those with lab-diagnosed diabetes, 30.9% were retained-in-care (based on diabetes labs) and 8.7% reached glycaemic control by 24-months. Prevalence of lab-diagnosed diabetes in PLWH was 28.6% versus 47.3% in PLWOH. Among those with lab-diagnosed diabetes, 34.3% of PLWH were retained-in-care versus 30.3% PLWOH. Among people retained-in-care, 33.8% of PLWH reached glycaemic control over 24-months versus 28.6% of PLWOH. CONCLUSIONS: In our analysis of South Africa's NHLS database, we observed that 70% of patients diagnosed with diabetes did not maintain in consistent diabetes care, with fewer than 10% reaching glycemic control within 24 months. We noted a disparity in diabetes prevalence between PLWH and PLWOH, potentially linked to different screening methods. These differences underscore the intricacies in care but also emphasize how HIV care practices could guide better management of chronic diseases like diabetes. Our results underscore the imperative for specialized strategies to bolster diabetes care in South Africa.