Introduction: The impact of defining secondhand smoke exposure among nonsmokers using an expanded serum cotinine range is currently unknown. Methods: This study assessed the trends in secondhand smoke exposure prevalence among a nationally representative sample of 23,753 U.S. nonsmokers aged ≥3 years. Serum cotinine ranges of 0.05–10 ng/mL (established) and of 0.015–10 ng/mL (expanded) were analyzed in 2021 using data from the 2011–2018 National Health and Nutrition Examination Survey. Results: During 2011–2018, the percentage of people with a serum cotinine range of 0.05–10 ng/mL remained stable (25.3% to 24.6%) across most sociodemographic subgroups but declined significantly among adult Mexican Americans aged ≥20 years (23.9% to 14.1%). However, the percentage of people with serum cotinine range of 0.015–10 ng/mL significantly declined (58.3% to 52.3%) among male individuals (60.9% to 55.0%), among female individuals (56.2% to 50.0%), among adults aged ≥20 years (55.8% to 49.2%), among Mexican Americans (60.9% to 41.2%), among people with a college degree or higher (44.4% to 36.0%), among those who rented their housing (71.7% to 62.5%), among people not living with someone who smoked inside the home (56.1% to 50.0%), and among Mexican Americans aged ≥20 years (60.9% to 39.1%) (all p<0.05 for linear trend test). Conclusions: Expanding the serum cotinine range to 0.015–10 ng/mL more than doubles the estimated proportion of U.S. nonsmokers exposed to secondhand smoke. In contrast to a serum cotinine range of 0.05–10 ng/mL, it suggests that progress has been made in reducing population-level secondhand smoke exposure during 2011–2018, especially among nonsmokers experiencing lower exposure levels. © 2021

PURPOSE: To examine the chemical composition of JUUL pods collected from a convenience sample of 16 high schools in California to identify possible consumer modification or counterfeit use. METHODS: Using Gas Chromatography-Mass Spectrometry, we quantitatively analyzed the nicotine, propylene glycol (PG), and vegetable glycerin (VG) in JUUL pods (n = 26) collected from California high schools and compared results to commercial 3% (n = 15) and 5% (n = 24) JUUL pods purchased online. RESULTS: Most of the collected JUUL pods (24/26 pods) had a nicotine concentration (43.3 mg/ml, 95% PI: 21.5-65.1) outside the prediction intervals (PI) of the 3% (33.5 mg/ml, 95% PI: 31.8-35.2) and 5% (55.0 mg/ml, 95% PI: 51.5-58.3) commercial JUUL pods. Most (73%) collected JUUL pods had VG concentrations (583.5 mg/ml, PI: 428.9-738.1) lower than the 3% (722.2 mg/ml, PI: 643.0-801.4) and 5% (710.5 mg/ml, PI: 653.1-767.8) commercial JUUL pods. CONCLUSIONS: Used JUUL products collected from high school students or found on school grounds were not chemically consistent with the manufacturer's stated formulations.

INTRODUCTION: A gradual reduction of cigarette nicotine content to nonaddictive levels has been proposed as an endgame strategy to accelerate declines in combustible tobacco smoking. We assessed manufacturer-reported nicotine yield in cigarettes sold in the United States from 2013 to 2016. METHODS: We merged machine-measured nicotine yield in cigarette smoke and pack characteristics obtained from reports filed by tobacco manufacturers with the Federal Trade Commission for 2013-2016 with monthly Nielsen data on US cigarette sales. Manufacturer-reported, sales-weighted, average annual nicotine yield was assessed, as were nicotine yield sales trends by quartile: markedly low (0.10-0.60 mg/stick), low (0.61-0.80 mg/stick), moderate (0.81-0.90 mg/stick), and high (0.91-3.00 mg/stick). Trends in overall, menthol, and nonmenthol pack sales, by nicotine yield quartiles over the study period and by year, were determined by using Joinpoint regression. RESULTS: During 2013-2016, average annual sales-weighted nicotine yield for all cigarettes increased from 0.903 mg/stick (95% CI, 0.882-0.925) in 2013 to 0.938 mg/stick (95% CI, 0.915-0.962) in 2016 (P < .05). For menthol cigarettes, yield increased from 0.943 mg/stick in 2013 (95% CI, 0.909-0.977) to 1.037 mg/stick in 2016 (95% CI, 0.993-1.081), increasing 0.2% each month (P < .05). Most pack sales occurred among high (41.5%) and low (30.7%) nicotine yield quartiles. Cigarette sales for the markedly low quartile decreased by an average of 0.4% each month during 2013-2016 (P < .05). CONCLUSION: During 2013-2016, manufacturer-reported, sales-weighted nicotine yield in cigarettes increased, most notably for menthol cigarettes. Continued monitoring of nicotine yield and content in cigarettes can inform tobacco control strategies.

E-cigarette, or vaping, products are electronic devices that produce an inhalable aerosol by heating an e-liquid that typically contains nicotine and other additives (1). Nicotine is highly addictive, can harm adolescent brain development, and can prime the brain for addiction to other drugs (1). In 2019, 27.5% of U.S. high school students currently used e-cigarettes (2), and 73.4% of high school students had observed e-cigarette use on school grounds (3). E-cigarette use among U.S. youths increased considerably during 2017–2019 (2). This rise coincided with the increased popularity of “pod mods,” which are products with a prefilled or refillable pod cartridge (pod) and a modifiable (mod) system. Pod mods typically use nicotine salts rather than the freebase nicotine used in most other e-cigarette, or vaping, products and conventional tobacco products (e.g., cigarettes).* Nicotine salts, which have a lower pH than freebase nicotine, allow particularly high levels of nicotine to be inhaled more easily and with less irritation to the throat than freebase nicotine.† The most commonly sold pod mod brand is JUUL, which accounted for 75% of all U.S. e-cigarettes sales by the end of 2018.§ A majority (59.1%) of U.S. high school student e-cigarette users report JUUL is their usual brand (2).

The Centers for Disease Control and Prevention (CDC), the US Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders have investigated a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). 1 As of February 25, 2020, a total of 2,807 hospitalized cases of EVALI have been reported to the CDC from all 50 states, the District of Columbia, and two US territories (Puerto Rico and US Virgin Islands). Sixty-eight deaths have been confirmed in 29 states and the District of Columbia (as of February 18, 2020).2, 3, 4, 5, 6 Mechanisms for lung injury in this syndrome are still being investigated. Vitamin E acetate (VEA) is strongly linked to the EVALI outbreak. VEA has been found in product samples tested by FDA and state laboratories and patient BAL fluid samples tested by the CDC from geographically diverse states. VEA has not been found in the BAL fluid of people who do not have EVALI. However, evidence is not sufficient to rule out the contribution of other chemicals of concern, including chemicals in either tetrahydrocannabinol (THC) or non-THC products, in some of the reported EVALI cases. The current article summarizes evidence as of February 25, 2020, for potential toxicants and mechanisms of toxicity for EVALI.

Importance: To date, limited information is available on the characteristics of adolescents with e-cigarette, or vaping, product use-associated lung injury (EVALI). Objective: To inform public health and clinical practice by describing differences in demographics, substance use behaviors, and clinical characteristics of EVALI among adolescents compared with adults. Design, Setting, and Participants: Surveillance data reported to the Centers for Disease Control and Prevention during the 2019 EVALI outbreak were used to calculate adjusted prevalence ratios (aPRs) with 95% CIs and to test differences between 360 hospitalized or deceased adolescents vs 859 young adults and 936 adults with EVALI (N = 2155). Main Outcomes and Measures: Demographics, substance use behaviors, and clinical characteristics. Results: Included in this cross-sectional study were 360 hospitalized or deceased adolescents (age range, 13-17 years; 67.9% male) vs 859 young adults (age range, 18-24 years; 72.4% male) and 936 adults (age range, 25-49 years; 65.6% male) with EVALI. Adolescents diagnosed as having EVALI reported using any nicotine-containing (62.4%), any tetrahydrocannabinol (THC)-containing (81.7%), and both (50.8%) types of e-cigarette or vaping products. Informal sources for obtaining nicotine-containing and THC-containing e-cigarette or vaping products were more commonly reported by adolescents (50.5% for nicotine and 96.5% for THC) than young adults (19.8% for nicotine [aPR, 2.49; 95% CI, 1.78-3.46] and 86.9% for THC [aPR, 1.11; 95% CI, 1.05-1.18]) or adults (24.3% for nicotine [aPR, 2.06; 95% CI, 1.49-2.84] and 75.1% for THC [aPR, 1.29; 95% CI, 1.19-1.40]). Mental, emotional, or behavioral disorders were commonly reported; a history of attention-deficit/hyperactivity disorder was almost 4 times more likely among adolescents (18.1%) than adults (4.9%) (aPR, 3.74; 95% CI, 1.92-7.26). A history of asthma was more likely to be reported among adolescents (43.6%) than adults (28.3%) (aPR, 1.53; 95% CI, 1.14-2.05). Gastrointestinal and constitutional symptoms were more common in adolescents (90.9% and 97.3%, respectively) than adults (75.3% and 94.5%, respectively) (aPR, 1.20; 95% CI, 1.13-1.28 and aPR, 1.03; 95% CI, 1.00-1.06, respectively). Because of missing data, percentages may not be able to be calculated from data provided. Conclusions and Relevance: Public health and clinical professionals should continue to provide information to adolescents about the association between EVALI and THC-containing e-cigarette or vaping product use, especially those products obtained through informal sources, and that the use of any e-cigarette or vaping product is unsafe. Compared with adults, it appears that adolescents with EVALI more frequently have a history of asthma and mental, emotional, or behavioral disorders, such as attention-deficit/hyperactivity disorder, and report nonspecific problems, including gastrointestinal and constitutional symptoms; therefore, obtaining a confidential substance use history that includes e-cigarette or vaping product use is recommended.

Since August 2019, CDC, the Food and Drug Administration (FDA), state and local health departments, and public health and clinical stakeholders have been investigating a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) (1). This report updates patient demographic characteristics, self-reported substance use, and hospitalization dates for EVALI patients reported to CDC by states, as well as the distribution of emergency department (ED) visits related to e-cigarette, or vaping, products analyzed through the National Syndromic Surveillance Program (NSSP). As of January 14, 2020, a total of 2,668 hospitalized EVALI cases had been reported to CDC. Median patient age was 24 years, and 66% were male. Overall, 82% of EVALI patients reported using any tetrahydrocannabinol (THC)-containing e-cigarette, or vaping, product (including 33% with exclusive THC-containing product use), and 57% of EVALI patients reported using any nicotine-containing product (including 14% with exclusive nicotine-containing product use). Syndromic surveillance indicates that ED visits related to e-cigarette, or vaping, products continue to decline after sharply increasing in August 2019 and peaking in September 2019. Clinicians and public health practitioners should remain vigilant for new EVALI cases. CDC recommends that persons not use THC-containing e-cigarette, or vaping, products, especially those acquired from informal sources such as friends, family members, or from in-person or online dealers. Vitamin E acetate is strongly linked to the EVALI outbreak and should not be added to any e-cigarette, or vaping, products (2). However, evidence is not sufficient to rule out the contribution of other chemicals of concern, including chemicals in either THC- or non-THC-containing products, in some reported EVALI cases.

On August 1, 2019, the first cases of electronic cigarette (e-cigarette), or vaping, product use–associated lung injury (EVALI) were reported to the Centers for Disease Control and Prevention (CDC).1 The cluster was an initial signal of an outbreak that by December 17, 2019, had resulted in 2506 cases involving hospitalized patients being reported to the CDC. Most patients with EVALI have been men and adolescent boys (67%), have been younger than 35 years of age (78%), and have reported using e-cigarette products containing tetrahydrocannabinol (THC) (80%).2

INTRODUCTION: Beginning September 3, 2014, CVS Health stopped selling tobacco products in all of its retail stores nationwide. This study assessed the impact of removing tobacco sales from CVS Health on cigarette smoking behaviors among U.S. adult smokers. METHODS: CVS Health retail location data (2012-2016) were linked with data from the Behavioral Risk Factor Surveillance System, a phone-based survey of the non-institutionalized civilian population aged >/=18 years. Using a difference-in-differences regression model, quit attempts and daily versus nondaily smoking were compared between smokers living in counties with CVS stores and counties without CVS stores, before and after CVS's removal of tobacco sales. Control variables included individuals' sociodemographic and health-related variables, state tobacco control variables, and urban status of counties. Analyses were conducted in 2018. RESULTS: During the 2-year period following the removal of tobacco sales from CVS Health, smokers living in counties with high CVS density (>/=3.5 CVS stores per 100,000 people) had a 2.21% (95% CI=0.08, 4.33) increase in their quit attempt rates compared with smokers living in counties without CVS stores. This effect was greater in urban areas (marginal effect: 3.03%, 95% CI=0.81, 5.25); however, there was no statistically significant impact in rural areas. Additionally, there was no impact on daily versus nondaily smoking in either urban or rural areas. CONCLUSIONS: Removing tobacco sales in retail pharmacies could help support cessation among U.S. adults who are attempting to quit smoking, particularly in urban areas.

On September 6, 2019, this report was posted as an MMWR Early Release on the MMWR website (https://www.cdc.gov/mmwr). As of August 27, 2019, 215 possible cases of severe pulmonary disease associated with the use of electronic cigarette (e-cigarette) products (e.g., devices, liquids, refill pods, and cartridges) had been reported to CDC by 25 state health departments. E-cigarettes are devices that produce an aerosol by heating a liquid containing various chemicals, including nicotine, flavorings, and other additives (e.g., propellants, solvents, and oils). Users inhale the aerosol, including any additives, into their lungs. Aerosols produced by e-cigarettes can contain harmful or potentially harmful substances, including heavy metals such as lead, volatile organic compounds, ultrafine particles, cancer-causing chemicals, or other agents such as chemicals used for cleaning the device (1). E-cigarettes also can be used to deliver tetrahydrocannabinol (THC), the principal psychoactive component of cannabis, or other drugs; for example, "dabbing" involves superheating substances that contain high concentrations of THC and other plant compounds (e.g., cannabidiol) with the intent of inhaling the aerosol. E-cigarette users could potentially add other substances to the devices. This report summarizes available information and provides interim case definitions and guidance for reporting possible cases of severe pulmonary disease. The guidance in this report reflects data available as of September 6, 2019; guidance will be updated as additional information becomes available.

Exposure to secondhand smoke from burning tobacco products can cause sudden infant death syndrome, respiratory infections, ear infections, and asthma attacks in infants and children, and coronary heart disease, stroke, and lung cancer in adult nonsmokers (1). There is no risk-free level of secondhand smoke exposure (2). CDC analyzed questionnaire and laboratory data from the National Health and Nutrition Examination Survey (NHANES) to assess patterns of secondhand smoke exposure among U.S. nonsmokers. The prevalence of secondhand smoke exposure among U.S. nonsmokers declined substantially during 1988-2014, from 87.5% to 25.2%. However, no change in exposure occurred between 2011-2012 and 2013-2014, and an estimated one in four nonsmokers, or approximately 58 million persons, were still exposed to secondhand smoke during 2013-2014. Moreover, marked disparities persisted across population groups. Exposure prevalence was highest among nonsmokers aged 3-11 years (37.9%), non-Hispanic blacks (50.3%), and those who were living in poverty (47.9%), in rental housing (38.6%), or with someone who smoked inside the home (73.0%), or among persons who had less than a high school education (30.7%). Comprehensive smoke-free laws and policies for workplaces and public places and smoke-free rules for homes and vehicles can further reduce secondhand smoke exposure among all nonsmokers.

Evidence suggests exposure of nicotine-containing e-cigarette aerosol to nonusers leads to systemic absorption of nicotine. However, no studies have examined acute secondhand exposures that occur in public settings. Here, we measured the serum, saliva and urine of nonusers pre- and post-exposure to nicotine via e-cigarette aerosol. Secondarily, we recorded factors affecting the exposure. Six nonusers of nicotine-containing products were exposed to secondhand aerosol from ad libitum e-cigarette use by three e-cigarette users for 2h during two separate sessions (disposables, tank-style). Pre-exposure (baseline) and post-exposure peak levels (Cmax) of cotinine were measured in nonusers' serum, saliva, and urine over a 6-hour follow-up, plus a saliva sample the following morning. We also measured solution consumption, nicotine concentration, and pH, along with use behavior. Baseline cotinine levels were higher than typical for the US population (median serum session one=0.089ng/ml; session two=0.052ng/ml). Systemic absorption of nicotine occurred in nonusers with baselines indicative of no/low tobacco exposure, but not in nonusers with elevated baselines. Median changes in cotinine for disposable exposure were 0.007ng/ml serum, 0.033ng/ml saliva, and 0.316ng/mg creatinine in urine. For tank-style exposure they were 0.041ng/ml serum, 0.060ng/ml saliva, and 0.948ng/mg creatinine in urine. Finally, we measured substantial differences in solution nicotine concentrations, pH, use behavior and consumption. Our data show that although exposures may vary considerably, nonusers can systemically absorb nicotine following acute exposure to secondhand e-cigarette aerosol. This can particularly affect sensitive subpopulations, such as children and women of reproductive age.

Background: Few studies have examined the extent of inhalation or dermal contact among bystanders following short-term, secondhand e-cigarette exposure. Objective: Measure PM2.5 (particles <2.5 microns), UF (ultrafine particles <100nm), and nicotine in air and deposited on surfaces and clothing pre-/during/post- a short-term (two-hour) e-cigarette exposure. Methods: E-cigarettes were used ad libitum by three experienced users for two hours during two separate sessions (disposable e-cigarettes, then tank-style e-cigarettes, or "tanks") in a 1858ft3 room. We recorded: uncorrected PM2.5 (using SidePak(R)); UF (using P-Trak(R)); air nicotine concentrations (using air samplers; SKC(R) XAD-4 canisters); ambient air exchange rate (using an air capture hood). Wipe samples were taken by wiping 100cm2 room surfaces pre- and post- both sessions, and clean cloth wipes were worn during the exposure and collected at the end. Results: Uncorrected PM2.5 and UF were higher (p<0.0001) during sessions than before or after. Median PM2.5 during exposure was higher using tanks (0.515mg/m3) than disposables (0.035mg/m3)(p<0.0001). Median UF during exposure was higher using disposables (31,200particles/cm3) than tanks (25,200particles/cm3)(p<0.0001). Median air nicotine levels were higher (p<0.05) during both sessions (disposables=0.697ng/L, tanks=1.833ng/L) than before (disposables=0.004ng/L, tanks=0.010ng/L) or after (disposables=0.115ng/L, tanks=0.147ng/L). Median accumulation rates of nicotine on surface samples were 2.1ng/100cm2/hr using disposables and 4.0ng/100cm2/hr using tanks; for cloth samples, it was 44.4ng/100cm2/hr using disposables and 69.6ng/100cm2/hr using tanks (p<0.01). Mean room ventilation rate was ~5 air changes per hour during both sessions. Conclusions: Short-term e-cigarette use can produce: elevated PM2.5; elevated UF; nicotine in the air; and accumulation of nicotine on surfaces and clothing. Implications: * Short-term indoor e-cigarette use produced accumulation of nicotine on surfaces and clothing, which could lead to dermal exposure to nicotine. * Short-term e-cigarette use produced elevated PM2.5 and ultrafine particles, which could lead to secondhand inhalation of these particles and any chemicals associated with them by bystanders. * We measured significant differences in PM2.5 and ultrafine particles between disposable e-cigarettes and tank-style e-cigarettes, suggesting a difference in the exposure profiles of e-cigarette products.

Background: E-cigarettes are battery-powered devices that deliver nicotine and flavorings by aerosol and have been marketed in the United States since 2007. Because e-cigarettes have increased in popularity, toxicity potential from device misuse and malfunction also has increased. National data indicate that during 2010–2014, exposure calls to US poison control centers increased only 0.3% for conventional cigarette exposures, whereas calls increased 41.7% for e-cigarette exposures. Methods: We characterized cigarette and e-cigarette exposure calls to the Wisconsin Poison Center January 1, 2010 through October 10, 2015. We compared cigarette and e-cigarette exposure calls by exposure year, demographic characteristics, caller site, exposure site, exposure route, exposure reason, medical outcome, management site, and level of care at a health care facility. Results: During January 2010 to October 2015, a total of 98 e-cigarette exposure calls were reported, and annual exposure calls increased approximately 17-fold, from 2 to 35. During the same period, 671 single-exposure cigarette calls with stable annual call volumes were reported. E-cigarette exposure calls were associated with children aged ≤5 years (57/98, 58.2%) and adults aged ≥20 years (30/98, 30.6%). Cigarette exposure calls predominated among children aged ≤5 years (643/671, 95.8%). Conclusion: The frequency of e-cigarette exposure calls to the Wisconsin Poison Center has increased and is highest among children aged ≤5 years and adults. Strategies are warranted to prevent future poisonings from these devices, including nicotine warning labels and public advisories to keep e-cigarettes away from children.

Electronic cigarettes (e-cigarettes) are now the most commonly used tobacco product among U.S. youths; in 2015, 5.3% of middle school students and 16.0% of high school students reported using e-cigarettes in the past 30 days. However, limited information exists on the e-cigarette product types and brands used and the substances used in these products by youths. CDC and the Food and Drug Administration (FDA) analyzed data from the 2015 National Youth Tobacco Survey (NYTS) to examine the characteristics of e-cigarette use among U.S. middle (grades 6-8) and high (grades 9-12) school students in 2015, including types of products used, brands of products used, and whether substances other than nicotine were used with the products. Among respondents reporting ever having used an e-cigarette, 14.5% used only disposable e-cigarettes, 53.4% used only rechargeable/refillable e-cigarettes, and 32.1% used both types. Two of the most commonly used e-cigarette brands were blu (26.4%, 1.65 million youths) and VUSE (12.2%, 760,000 youths); half of students (50.7%, 3.18 million) did not know the brand of e-cigarette they used. One third (32.5%) of those who reported ever using an e-cigarette also reported having used e-cigarettes for substances other than nicotine. Preventing youths from beginning use of any tobacco product, including e-cigarettes, is critical to tobacco use prevention and control strategies in the United States. Monitoring the characteristics of e-cigarette use among youths, including product types, brands, and ingredients, is important to inform strategies to prevent and reduce e-cigarette use among youths.

INTRODUCTION: E-cigarette use is increasing, and the long-term impact on public health is unclear. We described the acute adverse health effects from e-cigarette exposures reported to U.S. poison centers. METHODS: We compared monthly counts and demographic, exposure, and health effects data of calls about e-cigarettes and conventional cigarettes made to poison centers from September 2010 through December 2014. RESULTS: Monthly e-cigarette calls increased from 1 in September 2010, peaked at 401 in April 2014, and declined to 295 in December 2014. Monthly conventional cigarette calls during the same period ranged from 302 to 514. E-cigarette calls were more likely than conventional cigarette calls to report adverse health effects, including vomiting, eye irritation, and nausea. Five e-cigarette calls reported major health effects, such as respiratory failure, and there were two deaths associated with e-cigarette calls. CONCLUSION: E-cigarette calls to U.S. poison centers increased over the study period, and were more likely than conventional cigarettes to report adverse health effects. It is important for health care providers and the public to be aware of potential acute health effects from e-cigarettes. Developing strategies to monitor and prevent poisonings from these novel devices is critical.

BACKGROUND: Climate change has contributed to increasing temperatures, earlier snowmelts and thinning ice packs in the Arctic, where crossing frozen bodies of water is essential for transportation and subsistence living. In some Arctic communities, anecdotal reports indicate a growing belief that falling-through-the-ice (FTI) are increasing. The objective of this study was to describe the morbidity and mortality associated with unintentional FTIs in Alaska. METHODS: We searched newspaper reports to identify FTI events from 1990 to 2010. We also used data from a trauma registry, occupational health and law enforcement registries and vital statistics to supplement the newspaper reports. Morbidity and mortality rates were calculated for Alaska Native (AN) people and all Alaskans. RESULTS: During the 21-year period, we identified 307 events, affecting at least 449 people. Events ranged from no morbidity to fatalities of five people. More than half of the events involved transportation by snow machine. Mortality rates were markedly higher for AN people than that for all Alaskans. CONCLUSIONS: We provide a numeric estimate of the importance of FTI events in Alaska. FTIs may represent an adverse health outcome related to climate changes in the Arctic, and may be particularly critical for vulnerable populations such as AN people.

OBJECTIVE(S): We examined screening practices and attitudes of obstetricians-gynecologists toward the use of non-combusted tobacco products (chewing tobacco, snuff/snus, electronic cigarettes, and dissolvables) during pregnancy. STUDY DESIGN: The authors mailed a survey in 2012 to 1,024 members of the American College of Obstetricians and Gynecologists, including Collaborative Ambulatory Research Network (CARN)- and non-CARN members. Stratified random selection was used to generate CARN and non-CARN samples. RESULTS: Response rates were 52% and 31% for CARN and non-CARN members, respectively. Of 252 total eligible respondents (those currently providing obstetrical care) 53% reported screening pregnant women at intake for non-combusted tobacco product use all or some of the time, and 40% none of the time. Those reporting that non-combusted products have adverse health effects during pregnancy but are safer than cigarettes ranged from 20% (dissolvables) to 28% (electronic cigarettes), and that the health effects are the same as those of cigarettes from 13% (electronic cigarettes) to 52% (chewing tobacco). Approximately 14% reported that electronic cigarettes have no adverse health effects, while < 1% reported no health effects for the remaining products. Two-thirds wanted to know more about the potential health effects of non-combusted tobacco products; only 5% felt fully informed. CONCLUSIONS: A large proportion of obstetrician-gynecologists reported never or inconsistently screening their pregnant patients for use of non-combusted tobacco products. Responses regarding the harms of these products relative to cigarettes were mixed and most respondents wanted more information. Development and dissemination of guidance for providers is needed improve decision making regarding non-combusted tobacco products.

Electronic nicotine delivery devices such as electronic cigarettes (e-cigarettes) are battery-powered devices that deliver nicotine, flavorings (e.g., fruit, mint, and chocolate), and other chemicals via an inhaled aerosol. E-cigarettes that are marketed without a therapeutic claim by the product manufacturer are currently not regulated by the Food and Drug Administration (FDA) . In many states, there are no restrictions on the sale of e-cigarettes to minors. Although e-cigarette use is increasing among U.S. adolescents and adults, its overall impact on public health remains unclear. One area of concern is the potential of e-cigarettes to cause acute nicotine toxicity. To assess the frequency of exposures to e-cigarettes and characterize the reported adverse health effects associated with e-cigarettes, CDC analyzed data on calls to U.S. poison centers (PCs) about human exposures to e-cigarettes (exposure calls) for the period September 2010 (when new, unique codes were added specifically for capturing e-cigarette calls) through February 2014. To provide a comparison to a conventional product with known toxicity, the number and characteristics of e-cigarette exposure calls were compared with those of conventional tobacco cigarette exposure calls.

INTRODUCTION: Nodding Syndrome (NS), an unexplained illness characterized by spells of head bobbing, has been reported in Sudan and Tanzania, perhaps as early as 1962. Hypothesized causes include sorghum consumption, measles, and onchocerciasis infection. In 2009, a couple thousand cases were reportedly in Northern Uganda. METHODS: In December 2009, we identified cases in Kitgum District. The case definition included persons who were previously developmentally normal who had nodding. Cases, further defined as 5- to 15-years-old with an additional neurological deficit, were matched to village controls to assess risk factors and test biological specimens. Logistic regression models were used to evaluate associations. RESULTS: Surveillance identified 224 cases; most (95%) were 5-15-years-old (range = 2-27). Cases were reported in Uganda since 1997. The overall prevalence was 12 cases per 1,000 (range by parish = 0.6-46). The case-control investigation (n = 49 case/village control pairs) showed no association between NS and previously reported measles; sorghum was consumed by most subjects. Positive onchocerciasis serology [age-adjusted odds ratio (AOR1) = 14.4 (2.7, 78.3)], exposure to munitions [AOR1 = 13.9 (1.4, 135.3)], and consumption of crushed roots [AOR1 = 5.4 (1.3, 22.1)] were more likely in cases. Vitamin B6 deficiency was present in the majority of cases (84%) and controls (75%). CONCLUSION: NS appears to be increasing in Uganda since 2000 with 2009 parish prevalence as high as 46 cases per 1,000 5- to 15-year old children. Our results found no supporting evidence for many proposed NS risk factors, revealed association with onchocerciasis, which for the first time was examined with serologic testing, and raised nutritional deficiencies and toxic exposures as possible etiologies.

BACKGROUND: Nodding syndrome is an unexplained illness characterised by head-bobbing spells. The clinical and epidemiological features are incompletely described, and the explanation for the nodding and the underlying cause of nodding syndrome are unknown. We aimed to describe the clinical and neurological diagnostic features of this illness. METHODS: In December, 2009, we did a multifaceted investigation to assess epidemiological and clinical illness features in 13 parishes in Kitgum District, Uganda. We defined a case as a previously healthy child aged 5-15 years with reported nodding and at least one other neurological deficit. Children from a systematic sample of a case-control investigation were enrolled in a clinical case series which included history, physical assessment, and neurological examinations; a subset had electroencephalography (EEG), electromyography, brain MRI, CSF analysis, or a combination of these analyses. We reassessed the available children 8 months later. FINDINGS: We enrolled 23 children (median age 12 years, range 7-15 years) in the case-series investigation, all of whom reported at least daily head nodding. 14 children had reported seizures. Seven (30%) children had gross cognitive impairment, and children with nodding did worse on cognitive tasks than did age-matched controls, with significantly lower scores on tests of short-term recall and attention, semantic fluency and fund of knowledge, and motor praxis. We obtained CSF samples from 16 children, all of which had normal glucose and protein concentrations. EEG of 12 children with nodding syndrome showed disorganised, slow background (n=10), and interictal generalised 2.5-3.0 Hz spike and slow waves (n=10). Two children had nodding episodes during EEG, which showed generalised electrodecrement and paraspinal electromyography dropout consistent with atonic seizures. MRI in four of five children showed generalised cerebral and cerebellar atrophy. Reassessment of 12 children found that six worsened in their clinical condition between the first evaluation and the follow-up evaluation interval, as indicated by more frequent head nodding or seizure episodes, and none had cessation or decrease in frequency of these episodes. INTERPRETATION: Nodding syndrome is an epidemic epilepsy associated with encephalopathy, with head nodding caused by atonic seizures. The natural history, cause, and management of the disorder remain to be determined. FUNDING: Division of Global Disease Detection and Emergency Response, US Centers for Disease Control and Prevention.

BACKGROUND: Selenium is an element necessary for normal cellular function, but it can have toxic effects at high doses. We investigated an outbreak of acute selenium poisoning. METHODS: A case was defined as the onset of symptoms of selenium toxicity in a person within 2 weeks after ingesting a dietary supplement manufactured by "Company A," purchased after January 1, 2008. We conducted case finding, administered initial and 90-day follow-up questionnaires to affected persons, and obtained laboratory data where available. RESULTS: The source of the outbreak was identified as a liquid dietary supplement that contained 200 times the labeled concentration of selenium. Of 201 cases identified in 10 states, 1 person was hospitalized. The median estimated dose of selenium consumed was 41 749 microg/d (recommended dietary allowance is 55 microg/d). Frequently reported symptoms included diarrhea (78%), fatigue (75%), hair loss (72%), joint pain (70%), nail discoloration or brittleness (61%), and nausea (58%). Symptoms persisting 90 days or longer included fingernail discoloration and loss (52%), fatigue (35%), and hair loss (29%). The mean initial serum selenium concentration of 8 patients was 751 microg/L (reference range, < or =125 microg/L). The mean initial urine selenium concentration of 7 patients was 166 microg/24 h (reference range, < or =55 microg/24 h). CONCLUSIONS: Toxic concentrations of selenium in a liquid dietary supplement resulted in a widespread outbreak. Had the manufacturers been held to standards used in the pharmaceutical industry, it may have been prevented.