compared with those who have never used e-cigarettes, according to the first study to evaluate the association in a large, nationally representative population of young adults.
“The e-cigarette use and sleep deprivation association seems to have a dose-response nature as the point estimate of the association increased with increased exposure to e-cigarette,” Sina Kianersi, DVM, and associates at Indiana University, Bloomington, said in.
Sleep deprivation was 49% more prevalent among everyday users of e-cigarettes, compared with nonusers. Prevalence ratios for former users (1.31) and occasional users (1.25) also showed significantly higher sleep deprivation, compared with nonusers, they reported based on a bivariate analysis of data from young adults aged 18-24 years who participated in the 2017 and 2018 Behavioral Risk Factor Surveillance System surveys.
After adjustment for multiple confounders, young adults who currently used e-cigarettes every day were 42% more likely to report sleep deprivation than those who never used e-cigarettes, a difference that was statistically significant. The prevalence of sleep deprivation among those who used e-cigarettes on some days was not significantly higher (prevalence ratio, 1.08), but the ratio between former users and never users was a significant 1.17, the investigators said.
“The nicotine in the inhaled e-cigarette aerosols may have negative effects on sleep architecture and disturb the neurotransmitters that regulate sleep cycle,” they suggested, and since higher doses of nicotine produce greater reductions in sleep duration, “those who use e-cigarette on a daily basis might consume higher doses of nicotine, compared to some days, former, and never users, and therefore get fewer hours of sleep.”
Nicotine withdrawal, on the other hand, has been found to increase sleep duration in a dose-dependent manner, which “could explain the smaller [prevalence ratios] observed for the association between e-cigarette use and sleep deprivation among former and some days e-cigarette users,” Dr. Kianersi and associates added.
The bivariate analysis involved 18,945 survey respondents, of whom 16,427 were included in the fully adjusted model using 12 confounding factors.
SOURCE: Kianersi S et al. Addict Behav. 2020 Sep 6. .