The Longitudinal Relationships between Depression and Smoking in Hardcore Smokers Using Autoregressive Cross-Lagged Modeling

Jeong Won Han; Hanna Lee

doi:10.4040/jkan.2019.49.1.69

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Han and Lee: The Longitudinal Relationships between Depression and Smoking in Hardcore Smokers Using Autoregressive Cross-Lagged Modeling

Original Article

J Korean Acad Nurs 2019;49(1):69-79.

Published online: 15 January 2019

DOI: https://doi.org/10.4040/jkan.2019.49.1.69

The Longitudinal Relationships between Depression and Smoking in Hardcore Smokers Using Autoregressive Cross-Lagged Modeling

Jeong Won Han¹, Hanna Lee^2,

¹College of Nursing Science, Kyung Hee University, Seoul

²Department of Nursing, Changwon National University, Changwon, Korea

Address reprint requests to : Lee, Hanna Department of Nursing, Changwon National University, 20 Changwondaehak-ro, Uichang-gu, Changwon 51140, Korea Tel: +82-55-213-3572 Fax: +82-55-213-3579 E-mail: 2hanno@hanmail.net

Received 30 August 2018 Revised 7 January 2019 Accepted 8 January 2019

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

Abstract

Purpose

This study aimed to identify the directionality of the causal relationship and interaction between depression and amount of smoking over time in hardcore smokers using longitudinal descriptive analysis.

Methods

Secondary data from the Korean Welfare Panel Study were analyzed using autoregressive cross-lagged modeling. Participants included 342 hardcore smokers who participated in the 8th to 11th waves of the panel study.

Results

Analyses revealed that change(s) in depression levels according to time had a significant positive relationship with the total amount of smoking per day (β=.29, β=.19, β=.17, p<.001), while change(s) in total amount of smoking per day according to time had a significant positive relationship with depression (β=.43, β=.50, β=.38, p<.001). Analysis of the cross-lagged effect between depression and total amount of smoking per day showed that depression at one time point had a significantly positive relationship with the total amount of smoking per day at the next time point (β=.14, β=.13, β=.13, p=.021), and that the total amount of smoking per day at one time point had a significant positive relationship with depression at the next time point (β=.04, β=.04, β=.03, p=.044).

Conclusion

The findings in the present study confirmed a cross-interaction between depression and total amount of smoking per day in hardcore smokers. The present findings could be used to develop appropriate smoking-related interventions.

Keywords: Depression, Longitudinal Studies, Smoking

References

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Figure 1.

Autoregressive cross-lagged modeling.

Table 1.

Descriptive Statistics of Depression and Smoking Amount Over Time

Variables	M	SD	Skewness	SE	Kurtosis	SE
Depression 8^th	2.08	2.38	2.51	0.13	4.53	0.26
Depression 9^th	1.60	1.41	2.56	0.13	9.07	0.26
Depression 10^th	1.96	1.40	2.34	0.13	9.43	0.26
Depression 11^th	2.09	1.54	2.85	0.13	4.84	0.26
Smoking amount 8^th	23.35	7.04	2.37	0.13	6.26	0.26
Smoking amount 9^th	23.12	6.59	2.11	0.13	4.07	0.26
Smoking amount 10^th	22.43	4.27	2.53	0.13	9.05	0.26
Smoking amount 11^th	23.52	4.35	2.09	0.13	9.89	0.26

M=mean; SD=standard deviation; SE=standard error.

Table 2.

The Correlation between Depression and Smoking Amount

Variables	X1	X2	X3	X4	X5	X6	X7	X8
Variables	r (p)	r (p)	r (p)	r (p)	r (p)	r (p)	r (p)	r (p)
Depression 8^th	1
Depression 9^th	.395	1
	(<.001)
Depression 10^th	.385	.474	1
	(<.001)	(<.001)
Depression 11^th	.311	.346	.367	1
	(<.001)	(.003)	(<.001)
Smoking amount 8^th	.150	.244	.164	.192	1
	(.009)	(.007)	(.016)	(.043)
Smoking amount 9^th	.185	.108	.377	.110	.570	1
	(.008)	(.045)	(.007)	(.024)	(<.001)
Smoking amount 10^th	.062	.103	.180	.202	.336	.430	1
	(.026)	(.006)	(.007)	(.005)	(<.001)	(<.001)
Smoking amount 11^th	.117	.129	.170	.141	.262	.315	.375	1
	(.007)	(.003)	(.006)	(.025)	(<.001)	(<.001)	(<.001)

Table 3.

Multi-Fitness Comparison of ACLM for Depression and Smoking Amount

Model	χ²	df	NFI	CFI	TLI	RMSEA
Model 1	296.74	161	0.93	0.99	0.98	0.04
Model 2	294.15	158	0.93	0.99	0.98	0.05
Model 3	286.60	157	0.93	0.99	0.98	0.04
Model 4	306.94	159	0.93	0.99	0.98	0.05
Model 5	330.24	161	0.93	0.98	0.98	0.05
Model 6	330.74	163	0.93	0.98	0.98	0.05
Model 7	332.02	165	0.93	0.98	0.98	0.05
Model 8	334.32	167	0.93	0.98	0.98	0.05

ACLM=Autoregression Cross-Lagged Model; df=Degree of freedom; NFI=Normal Fit Index; CFI=Comparative Fit Index; TLI=Turker-Lewis Index; RMSEA=Root Mean Squared Error of Approximation.

Table 4.

Parameter Estimation of ACLM between Depression and Smoking Amount

Pathway	B	β	CR	p
Depression 8^th → Depression 9^th	0.18	0.29	7.45	<.001
Depression 9^th → Depression 10^th	0.18	0.19	7.45	<.001
Depression 10^th → Depression 11^th	0.18	0.17	7.45	<.001
Smoking amount 8^th → Smoking amount 9^th	0.37	0.43	15.99	<.001
Smoking amount 9^th → Smoking amount 10^th	0.37	0.50	15.99	<.001
Smoking amount 10^th → Smoking amount 11^th	0.37	0.38	15.99	<.001
Depression 8^th → Smoking amount 9^th	0.12	0.14	2.31	.021
Depression 9^th → Smoking amount 10^th	0.12	0.13	2.31	.021
Depression 10^th → Smoking amount 11^th	0.12	0.13	2.31	.021
Smoking amount 8^th → Depression 9^th	0.06	0.04	2.01	.044
Smoking amount 9^th → Depression 10^th	0.06	0.04	2.01	.044
Smoking amount 10^th → Depression 11^th	0.06	0.03	2.01	.044

ACLM=Autoregression Cross-Lagged Model; CR=Construct reliability.

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