Associations between Sleep Duration and Smoked Cigarettes per Day, Heavy Smoking in Smokers

Article information

Korean J Health Promot. 2018;18(1):1-6

Publication date (electronic) : 2018 March 31

doi : https://doi.org/10.15384/kjhp.2018.18.1.1

Jae-Geon Yu , Chang-Gon Kim , Seung-Pil Jung , Keun-Mi Lee

Department of Family Medicine, Yeungnam University Medical Center, Yeungnam University College of Medicine, Daegu, Korea.

Corresponding author: Seung-Pil Jung, MD, PhD. Department of of Family Medicine, Yeungnam University Medical Center, Yeungnam University College of Medicine, 170 Hyeonchung-ro, Nam-gu, Daegu 42415, Korea. Tel: +82-53-620-3182, Fax: +82-53-623-8050, rokanten@outlook.kr

Received 2018 January 08; Accepted 2018 March 12.

Abstract

Background

This study was performed to evaluate the associations between sleep duration and smoked cigarettes per day, prevalence of heavy smoking.

Methods

This study was based on the data of 9,893 subjects who are currently smoking, from the 4th to 6th Korea National Health and Nutrition Examination Survey. Based on appropriate sleep duration from National Sleep Foundation, study subjects were categorized into short, appropriate and over sleep group. Multiple regression analysis was performed to evaluate the association between sleep duration and smoked cigarettes per day, prevalence of heavy smoking. Age, gender, household income, education, marital status, occupation, alcohol use, body weight, hypertension, diabetes mellitus, depression, and level of stress were controlled.

Results

Compared with appropriate sleep group, smoked cigarettes per day and prevalence of heavy smoking were higher in short sleep group, and lower in over sleep group.

Conclusions

There is association between sleep duration and smoked cigarettes per day, prevalence of heavy smoking.

Keywords: Cigarette smoking; Sleep; Dyssomnias

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Table 1

General characteristics of study subjects according to sleep duration

Values are presented as mean±standard deviation or number (%).

^aCalculated by chi-square test except Age by ANOVA.

Table 2

Smoking characteristics of study subjects according to sleep duration

Values are presented as mean±standard deviation or number (%).

^aCalculated by ANOVA.

^bCalculated by chi-square test.

Table 3

Results of multiple logistic regression of heavy smoking according to sleep duration

Abbreviations: OR, odds ratio; CI, confidence interval.

^aAdjusted for gender, age, household income, education, marital status, occupation, alcohol use, body weight, hypertension, diabetes mellitus, depression, and level of stress.

^bOR and 95% CI were calculated with multiple logistic regression.