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Analysis technique e-liquid samples number Nicotine level labeled (mg/mL) >10% difference between actual and labeled nicotine conc. Percent deviation Country Etter et al. [ 24 ] e-cigarette liquid UHPLC–DAD 20 6–30 2 −15 to 21% Sweden Davis et al. [ 27 ] e-cigarette

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Health 2015; 218: 169–180. 2 Margham J, McAdam K, Forster M, et al. Chemical composition of aerosol from an e-cigarette: a quantitative comparison with cigarette smoke. Chem Res

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A dohányzás és az e-cigaretta-használat epidemiológiája a felnőtt magyar népesség körében 2018-ban

The epidemiology of smoking and e-cigarette use in the Hungarian adult population in 2018

Orvosi Hetilap
Authors:
Zoltán Brys
,
Gergely Tóth
,
Róbert Urbán
,
József Vitrai
,
Gábor Magyar
,
Márta Bakacs
,
Zombor Berezvai
,
Csaba Ambrus
, and
Melinda Pénzes

R. E-cigarette – information for practicing physicians. [E-cigaretta – információ gyakorló orvosok számára.] Orvostovábbk Szle 2019; 26: 58–64. [Hungarian] 9

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abolition. University of California Press, Berkeley and Los Angeles, 2011. 3 Grana, R., Benowitz, N., Glantz, S. A.: E-cigarettes. A scientific review. Circulation

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A cigaretta, az elektromos cigaretta és a vízipipa egészségre gyakorolt hatása

Health effects of cigarettes, electronic cigarettes and waterpipes

Orvosi Hetilap
Authors:
Árpád Farkas
,
Gábor Tomisa
,
Erika Kis
, and
Alpár Horváth

] 33 Palamidas A, Tsikrika S, Katsaounou PA, et al. Acute effects of short term use of e-cigarettes on airways physiology and respiratory symptoms in smokers with and without airway obstructive

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References 1 Layden JE, Ghinai I, Pray I, et al. Pulmonary illness related to E-cigarette use in Illinois and Wisconsin – preliminary report. N Engl J Med. 2019 Sep 6

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e-cigarette, or vaping, product use-associated lung injury – United States, November 2019. Morb Mortal Wkly Rep. 2019; 68: 1076–1080. 2 Krishnasami VP, Hallowell BD

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Journal of Behavioral Addictions
Authors:
Steve Sussman PhD, FAAHB, FAPA
,
Thalida Em Arpawong
,
Ping Sun
,
Jennifer Tsai
,
Louise A. Rohrbach
, and
Donna Spruijt-Metz

Abstract

Background and Aims

Recent work has studied multiple addictions using a matrix measure, which taps multiple addictions through single responses for each type.

Methods

The present study investigated use of a matrix measure approach among former alternative high school youth (average age = 19.8 years) at risk for addictions. Lifetime and last 30-day prevalence of one or more of 11 addictions reviewed in other work (Sussman, Lisha & Griffiths, 2011) was the primary focus (i.e., cigarettes, alcohol, other/hard drugs, eating, gambling, Internet, shopping, love, sex, exercise, and work). Also, the co-occurrence of two or more of these 11 addictive behaviors was investigated. Finally, the latent class structure of these addictions, and their associations with other measures, was examined.

Results

We found that ever and last 30-day prevalence of one or more of these addictions was 79.2% and 61.5%, respectively. Ever and last 30-day co-occurrence of two or more of these addictions was 61.5% and 37.7%, respectively. Latent Class Analysis suggested two groups: a generally Non-addicted Group (67.2% of the sample) and a “Work Hard, Play Hard”-addicted Group that was particularly invested in addiction to love, sex, exercise, the Internet, and work. Supplementary analyses suggested that the single-response type self-reports may be measuring the addictions they intend to measure.

Discussion and Conclusions

We suggest implications of these results for future studies and the development of prevention and treatment programs, though much more validation research is needed on the use of this type of measure.

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Background and Aims

Recent work has studied addictions using a matrix measure, which taps multiple addictions through single responses for each type. This is the first longitudinal study using a matrix measure.

Methods

We investigated the use of this approach among former alternative high school youth (average age = 19.8 years at baseline; longitudinal n = 538) at risk for addictions. Lifetime and last 30-day prevalence of one or more of 11 addictions reviewed in other work was the primary focus (i.e., cigarettes, alcohol, hard drugs, shopping, gambling, Internet, love, sex, eating, work, and exercise). These were examined at two time-points one year apart. Latent class and latent transition analyses (LCA and LTA) were conducted in Mplus.

Results

Prevalence rates were stable across the two time-points. As in the cross-sectional baseline analysis, the 2-class model (addiction class, non-addiction class) fit the data better at follow-up than models with more classes. Item-response or conditional probabilities for each addiction type did not differ between time-points. As a result, the LTA model utilized constrained the conditional probabilities to be equal across the two time-points. In the addiction class, larger conditional probabilities (i.e., 0.40–0.49) were found for love, sex, exercise, and work addictions; medium conditional probabilities (i.e., 0.17–0.27) were found for cigarette, alcohol, other drugs, eating, Internet and shopping addiction; and a small conditional probability (0.06) was found for gambling.

Discussion and Conclusions

Persons in an addiction class tend to remain in this addiction class over a one-year period.

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Dohányzó várandósok elsődleges védőnői állapotfelmérése az alapellátásban

Tobacco smoking primary survey of pregnant women in the maternity and child health service

Orvosi Hetilap
Authors:
Ildikó Rákóczi
,
Péter Balázs
, and
Kristie L. Foley

://www.euro.who.int/en/health-topics/disease-prevention/tobacco/data-and-statistics [accessed: January 8, 2024]. 2 Brys Z, Tóth G, Urbán R. The epidemiology of smoking and e-cigarette use in the Hungarian adult population in 2018. [A dohányzás és az

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