The relationship between poor sleep quality measured by the Pittsburgh Sleep Quality Index and smoking status according to sex and age: an analysis of the 2018 Korean Community Health Survey

Abstract

Objectives: Multiple studies have found that cigarette smokers are more likely to experience sleep disturbances than non-smokers. This study aimed to examine various associations between smoking and sleep quality according to sex and age, which have yet to be sufficiently examined in prior studies.

Methods: Data analysis was conducted using a nationally representative sample of 224,986 Korean adults who participated in the 2018 Korea Community Health Survey. Sleep quality, as the dependent variable, was measured using the Pittsburgh Sleep Quality Index (PSQI), with PSQI scores indicating either good (≤4 points) or poor (>5 points) sleep quality. Multiple logistic regression analysis was performed considering socio-demographic factors, health behaviors, comorbidities, and psychological factors as covariates.

Results: The overall weighted prevalence of poor sleep quality was 39.4% (95% confidence interval, 39.1 to 39.7). In the multivariate model that excluded psychological factors, poor sleep quality positively correlated to smoking for both sexes and all age groups except for male aged ≥65 years. However, in the full model that included psychological factors, statistically significant odds ratios (approximately 1.5) for poor sleep quality according to smoking status were only observed for female under 65 years of age.

Conclusions: The relationship between poor sleep quality and smoking status differed according to sex and age. In order to improve the quality of sleep, it is necessary to intervene smoking cessation along with solving psychological problems, especially female in middle age and younger.

Keywords: Age group; Pittsburgh Sleep Quality Index; Sex; Sleep quality; Smoking behavior.

Figure 1.

Adjusted odds ratios (ORs) for poor sleep quality by smoking frequency/amount and age group (A: male, B: female). ¹Adjusted for frequency of age, education level, employment, alcohol consumption, walking exercise, history of hypertension or diabetes, perceived stress level, depressive mood, and subjective health status.