The Effects of Smokers Switching Behaviour on Health-Related Symptom Burden and Quality of Life: Analysis of US Prospective Longitudinal Cohort Study Data

doi:10.21203/rs.3.rs-3456580/v1

Background

Ecigarette (EC) use is rising, and evidence increasingly supports that ECs are helpful in smoking cessation. However, evidence concerning the longterm health effects of conventional cigarette smokers who switch to using ECs, and changes in healthrelated symptoms and quality of life (QoL), are lacking.

Objective

To examine the effects of switching from smoking to using ECs on healthrelated symptoms (fatigue, pain, and emotional problems) and general QoL.

Methods

We analysed data from 7,122 adult respondents in the U.S. Population Assessment of Tobacco and Health (PATH) study. These were exclusive cigarette smokers at Wave 1 and were followed up at any of Waves 2 to 5. At the followup waves, respondents were categorised into four groups based on their switching behaviours: (1) full switching (switching to exclusive EC use); (2) partial switching (switching to dual use of cigarettes and ECs); (3) quitting (not beginning EC use); and (4) nonswitching (exclusive cigarette smoking). Linear mixedeffects models controlling for age, sex, race, level of education and time were used to calculate adjusted mean differences (aMD) with 95% confidence intervals (CI) in general QoL and related factors between nonswitching and switching groups.

Results

Compared to nonswitching, full switching was significantly associated with less fatigue (aMD − 0.092; CI -0.167 to -0.017; P = 0.016), less emotional problems (aMD − 0.089; CI -0.175 to -0.002; P = 0.044), better QoL (aMD − 0.124; CI -0.193 to -0.056; P < 0.001), but similar pain (aMD − 0.156; CI -0.351 to 0.038; P = 0.108). No significant differences were observed between partial switching and nonswitching groups for fatigue, pain, emotional problems, or QoL (P > 0.05 in all cases). Those who quitted smoking and did not begin EC use reported the lowest fatigue, pain, and emotional problems, and the best QoL, among the four groups (all P < 0.001).

Conclusions

Smokers who quitted smoking or fully switched to using ECs had less healthrelated symptoms and better QoL than those who continued smoking. This impact on QoL should be taken into account when assessing the harm reduction potential of ECs, and the development of practices to help smokers switch and improve their QoL also needs to be considered.

ecigarettes

tobacco

harm reduction

symptom burden

quality of life

Despite decades of tobacco control efforts to reduce smokingrelated harms, cigarette smoking is still the leading global cause of death and disease. Without further efforts to reduce the prevalence of cigarette smoking, it is predicted that smoking may cause up to 1 billion deaths this century (Koh and Fiore, 2022). Cigarette smoking is a recognised risk factor for cardiovascular disease, chronic obstructive pulmonary disease (COPD) and lung cancer, along with many other human diseases (International Agency for Research on Cancer, 2007; World Health Organization, 2011; US Department of Health and Human Services, 2014). Nicotine, a chemical released from tobacco during smoking, is not considered to be responsible for smokingrelated disease, although its use is known to be addictive (Gottlieb and Zeller, 2017). Instead, smokinginduced diseases are primarily initiated by prolonged inhalational exposure to the numerous chemical toxicants found in cigarette smoke (Institute of Medicine, 2001; Stratton et al, 2001; Perfetti, 2011; Gottlieb and Zeller, 2017), which are formed during the process of combustion and have recognised links to human diseases (Food and Drug Administration, 2012).

Electronic cigarettes (ecigarettes; ECs) are battery powered devices which heat a liquid solution, commonly containing nicotine, to produce an inhalable vapour (Breland et al, 2017). Since EC liquids do not contain tobacco, and also since the process of vapour formation involves heating and not combustion, EC vapor contains far fewer chemical toxicants than cigarette smoke, and those that are present are found at significantly lower levels (Margham et al, 2016; National Academies of Sciences Engineering and Medicine, 2018; Theron et al, 2019). In smokers who completely switch to using ECs, both crosssectional and longitudinal studies have demonstrated that toxicant exposure is significantly reduced, and toxicant exposure among those who have switched can approach levels seen either with smoking cessation or among nonsmokers (Shahab et al, 2017; Goniewicz et al, 2018; Smith et al, 2020; Cohen et al, 2021; McEwan et al, 2021; Morris et al, 2021; Holt et al, 2023). Thus, ECs are a reduced exposure alternative for cigarette smokers and may help to reduce smokingrelated disease risk (Murphy et al, 2017; Camacho et al, 2021; Mendez and Warner, 2021; Edmiston et al, 2022; Kanobe et al, 2022; McNeill et al, 2022; Haswell et al, 2023; Holt et al, 2023; Kanobe et al, 2023). Furthermore, increasing evidence suggests that ECs can assist with smoking cessation (Chan et al, 2021; Hartmann-Boyce et al, 2022; Kotz et al, 2022; Carpenter et al, 2023; Warner et al, 2023), and this is supportive of a potential role for ECs in tobacco harm reduction efforts.

While smoking is associated with a significantly increased risk of developing smokingrelated disease, smoking cessation can, in the shortterm, lead to reductions in quality of life (QoL) and this may promote relapse and lead to failed cessation attempts (Shaw et al, 2001). However, those smokers who, during a cessation attempt, experience the largest increases in QoL factors such as physical functioning, general health and vitality may be more likely to remain abstinent longterm (Shaw et al, 2001). In addition, scores for these QoL domains, as well as other domains including mental health and bodily pain, are higher among former smokers than among current smokers (Olufade et al, 1999). Furthermore, some QoL domain scores, particularly those related to symptoms and the impact of smoking on QoL, were improved among former smokers compared with current smokers (Ware et al, 2015). Therefore, as well as reducing disease risk, quitting smoking also enhances QoL (Goldenberg, Danovitch and IsHak, 2014) and this should be taken into account when attempting to determine the harm reduction potential of products such as ECs which may assist with smoking cessation.

Few studies have examined changes in QoL in smokers who switch to using reduced risk tobacco and nicotine products. Using data from the United States (US) Population Assessment of Tobacco and Health (PATH) survey study, Price et al (2023) assessed differences in QoL among adults with a previous selfreported cancer diagnosis who were either current smokers or current EC users. This crosssectional analysis found that current smokers experienced greater fatigue, pain, emotional problems and general QoL than former or never smokers, and also that current EC use was associated with greater fatigue, pain, and emotional problems, but not general QoL, compared with nonuse (Price et al, 2023). However, that study did not examine differences in QoL and associated factors between smokers who had switched to using ECs or remained smoking, nor did they assess changes in QoL over time. Another crosssectional analysis, using data from a survey study which administered an abbreviated version of the World Health Organization Quality of Life instrument (WHOQOLBREF) to college students who used ECs or smoked cigarettes, demonstrated that exclusive cigarette smokers had significantly lower general QoL scores, as well as reduced scores for psychological, social relation and environmental health factors, than tobacco and nicotine product nonusers (Ridner et al, 2018). In addition, this study also found that scores in these domains, as well as physical health, were not significantly different between EC users and tobacco/nicotine nonusers (Ridner et al, 2018). Again however, the crosssectional used in that study did not assess either changes in QoL over time among cigarette smokers switching to EC use or differences between EC users and smokers. A longitudinal approach has been taken though to assess physical function, a factor of importance to QoL, using a 6minute walk distance (6MWD) test among smokers with COPD who switched to using either ECs or heated tobacco products (Polosa et al, 2016; Polosa et al, 2018; Polosa et al, 2021). For both products, switching caused significant improvements in 6MWD.

Since cigarette smoking reduces QoL, longterm smoking abstinence improves QoL, and QoL is not different between ecigarette users and nonusers, the aim of this study was to assess longitudinal changes in QoL among smokers who switched to using ECs. Using data from the US nationallyrepresentative PATH survey study, we examine changes in QoL factors in adult exclusive cigarette smokers who either partially or fully switch to using ECs, or who quit smoking completely and compare these with QoL factor scores among those who remain cigarette smoking. The findings of this analysis may be of importance when considering the harm reduction potential of ECs.

Data source and study sample

The PATH study is a nationally representative longitudinal cohort study of adult and youth tobacco use patterns and behaviours and health outcomes in the US (Hyland et al, 2017). The PATH study used a four‑stage stratified area probability sample design in Wave 1, consisting of a stratified sample of geographical primary sampling units (PSUs) at the first stage, smaller geographical segments at the second stage, residential addresses located in the segments at the third stage, and households within the residential addresses at the last stage. As part of the complex sample design, survey weights for participants were constructed to compensate for variable probabilities of selection, differential non‑response rates, and possible deficiencies in the sampling frame. The first wave of the PATH study was conducted between 2013 and 2014, Wave 2 was conducted between 2014 and 2015, Wave 3 was conducted between 2015. And 2016, Wave 4 was conducted between 2016 and 2018 with a replenishment sample to supplement the Wave 1 sample, and Wave 5 was conducted between 2018 and 2019. Our analyses included 7,122 current established exclusive cigarette smokers (defined as those who had smoked >100 cigarettes in their entire life and who reported both currently smoking cigarettes every day or some days and not currently using e‑cigarettes (EC)) at baseline (Wave 1), and those who completed the interview at any of the following four waves, Waves 2 to 5.

Study variables

Sociodemographic variables

The following variables were selected into this study: age (18‑24, 25‑44, or 45 years old or older), sex (male or female), race (white alone, black alone, or other race), ethnicity (Hispanic or not Hispanic), education level (less than bachelor’s degree or bachelor’s/advanced degree), total household income in the past 12 months (less than $50,000 or $50,000 or more), health insurance coverage (yes or no), and visited an emergency room or urgent care centre for a health problem of their own in the past 12 months (yes or no).

Switching behaviours

The main independent variable of interest was respondents’ switching behaviour at each wave compared to baseline. Respondents were divided into four categories at each wave were as follows: (1) full switching (switching from exclusive cigarette smoking to exclusive EC use); (2) partial switching (switching to dual use of cigarettes and ECs); (3) quitting (smoking cessation without any EC use); (4) non‑switching (continuing exclusive cigarette smoking).

Symptom burden

PATH survey questions relevant to symptom burden contained single‑item assessments of fatigue, pain, and emotional problems adapted from validated questionnaires in the PROMIS suite of measures, as follows:

Fatigue

Respondents were asked to rate their fatigue (“feeling unrested or overly tired during the day, no matter how many hours of sleep you’ve had”) on average in the past 7 days on a scale of 1 to 5, with 1 being no fatigue and 5 being very severe fatigue.

Pain

Respondents were asked to rate their pain on average in the past 7 days on a scale from 1 (“no pain”) to 10 (“the worst pain imaginable”).

Emotional problems

Respondents were asked how often they’ve been “bothered by emotional problems such as feeling anxious, depressed, or irritable” in the past 7 days on a scale of 1 (“never”) to 5 (“very often”).

Quality of life

Respondents were asked to rate their quality of life (QoL; “feeling unrested or overly tired during the day, no matter how many hours of sleep you’ve had”) in general on a scale from 1 (excellent) and 5 (poor), with higher scores indicating worse QoL.

Statistical Analyses

Unweighted values as well as percentages and weighted percentages were reported for socio‑demographic characteristics within the sample from Wave 1 to Wave 5. The 100 balanced repeated replicate (BRR) weights with Fay’s correction factor of 0.3 were used to calculate the 95% CIs for the weighted percentages. Weighted prevalence was estimated for each type of tobacco switching behaviour (full switching, partial switching, quitting, and non‑switching) for respondents in each follow up wave who were current established exclusive cigarette smokers at Wave 1. Single‑wave sampling weights were included when estimating the prevalence to account for complex survey design and to represent the whole U.S. population. Pearson’s Chi‑square tests were used to examine changes in prevalence across different time points.

To compare fatigue, pain, emotional problems, and QoL among those respondents with different switching behaviours, four linear mixed‑effects models controlling for baseline symptom burden and QoL scores, switching behaviours, age, sex, race, and level of education were established, with a random intercept for respondents and wave, and a random slope for baseline score at each wave. Least‑squared mean differences in fatigue, pain, emotional problems and QoL between the non‑switching group and the switching groups (full switching, partial switching, and quitting) were reported with 95% CIs. Each variable had extremely low proportion of missing values; therefore, analyses were performed on all available cases. P values < 0.05 were considered statistically significant. All statistical analyses were conducted using R Statistical Software (version 4.3.0 for Windows).

Demographics

Brief sociodemographic characteristics of the 7,122 established current cigarette smokers at baseline (PATH study Wave 1) whose data were analysed in this study are presented in Table 1. Approximately half of the selected respondents were female, and the majority were aged 25 years or older. The analytic sample were predominantly of White race and not Hispanic. The majority were educated to a level lower than bachelor’s degree level and had a total household income of less than $50,000. Three‑quarters of respondents had health insurance coverage, and a third had visited an emergency room or urgent care centre in the past 12 months for a health problem of their own.

Switching Behaviours

Data concerning switching behaviours of respondents in the analytical sample are presented in Table 2. Across waves, non‑switching was the predominant behaviour. At Wave 2, approximately three‑quarters of baseline (Wave 1) exclusive smokers remained smoking cigarettes. The proportion on non‑switching respondents declined across waves, reaching approximately 62% at Wave 5. Full switching (i.e., switching from exclusive smoking at Wave 1 to exclusive EC use at subsequent waves) increased over time, from 1.7% (weighted) of respondents at Wave 2 to 4.2% at Wave 5, and quitting smoking completely also increased over time, from 9.9% of respondents at Wave 2 to 22.4% at Wave 5. Partial switching was similar across waves, ranging from 9.4 to 12.1% of respondents. Initially, a downward trend in partial switching was seen in Waves 2 to 4, but this was reversed in Wave 5.

Impact of Switching Behaviours on Outcome Variables

Assessments were made of the impact of switching behaviours (full switching to exclusive EC use, partial switching, quitting smoking) compared with remaining smoking on the outcome variables of fatigue, pain, emotional problems and QoL. Data from mixed‑effects regression models, both unadjusted and adjusted for a number of covariates, are presented in Table 3. In addition, the mean outcome variables over time for each of the switching groups are presented in Figure 1. Generally speaking, mean outcome variable scores among those respondents who had quit smoking were lowest, and this was apparent across waves. Those who remained smoking cigarettes also generally had higher mean outcome variable scores across waves (Figure 2). The exception was for QoL scores, which were similar across waves between the full switching and quitting groups, and also between the non‑ and partial‑switching groups (Figure 2D).

With the adjusted regression model and compared with non‑switching, partial switching from cigarette smoking to dual use of cigarettes and ECs had no significant impact on each of the four outcome variables, i.e., the mean differences were not significantly different (Table 3). Full switching caused significant reductions in fatigue, emotional problems, and improved QoL (Table 3). Full switching had no effect on pain scores, although a significant reduction in pain was seen in the unadjusted model. Quitting smoking completely and not using ECs caused significant reductions in pain, fatigue, emotional problems, and improved QoL over time, in both the adjusted and unadjusted models (Table 3).

In this study, using data from the nationallyrepresentative PATH study we confirm that quitting smoking improves both general QoL and factors associated with QoL such as pain, fatigue, and emotional problems, which are consistent with the results of previous studies (Olufade et al, 1999; Shaw et al, 2001; Goldenberg, Danovitch and IsHak, 2014; Ware et al, 2015). In addition, we add to the previous findings and demonstrate that switching from smoking to EC use is associated with improved general QoL, as well as reduced fatigue and emotional problems. Switching from cigarette smoking to EC use may reduce toxicant exposure (Shahab et al, 2017; Goniewicz et al, 2018; Smith et al, 2020; Cohen et al, 2021; McEwan et al, 2021; Morris et al, 2021; Holt et al, 2023), is associated with beneficial changes in biomarkers of potential harm (Edmiston et al, 2022; Kanobe et al, 2022; Haswell et al, 2023; Kanobe et al, 2023), and thus may improve smokers’ health.

These findings are important when taking into account the proportion of smokers who are able to quit unaided compared with those who are able to quit using ECs. Quitting smoking unaided is inherently difficult, and increasing evidence supports that the likelihood of making a successful quit attempt is significantly higher when ECs are used to support smoking cessation compared with unaided quitting (Chan et al, 2021; Hartmann-Boyce et al, 2022; Kotz et al, 2022). In addition, during the early stages of quit attempts, reductions in QoL may promote relapse and lead to failed cessation attempts (Shaw et al, 2001). Overall, our findings give rise to the possibility that ECs may support smoking cessation and prevent relapse by increasing QoL and reducing factors which can influence QoL such as fatigue and emotional problems. Additionally, our findings also suggest that QoL and related factors should be taken into account when attempting to determine the full harm reduction potential of ECs.

In another analysis of PATH study data, focussing on those respondents who were cancer survivors (i.e., who selfreported a history of cancer), fatigue, pain, emotional problems and general QoL were higher among current smokers than among former and never smokers. Fatigue, pain, and emotional problems, were also higher among current EC users compared with non-users (Price et al, 2023), although that particular finding contrasts with other findings suggesting that both multi-factorial assessments of QoL (Ridner et al, 2018), as well as individual assessments of general QoL (Ridner et al, 2018), were not different between EC users and non-users. In the study by Price et al (2023), general QoL and associated factors were not examined between exsmoking current EC users and current smokers. Furthermore, the studies by Price et al (2023) and Ridner et al (2018) used crosssectional approaches and did not assess changes in QoL and associated factors over time. In another study, improvements in 6MWD, a factor which may be indicative of, and correlates with, QoL in patients with chronic lung disease (Kaplan et al, 2004), were observed among COPD patients in a longitudinal study who switched to using ECs for 24 and 36 months (Polosa et al, 2016; Polosa et al, 2018). Overall, our findings concur with these previous longitudinal study findings, while adding novel insight by being the first study to examine changes in QoL among smokers in the general population who completely switched to using ECs.

Our study has several strengths, including using nationallyrepresentative survey datasets comprising large numbers of respondents to assess changes in health status indicators and selfperceived QoL associated with switching from cigarette smoking to EC use. In addition, our longitudinal analysis facilitated an examination of changes in health status indicators and QoL among established smokers over time and subsequent to complete switching to EC use.

The findings of our analyses of PATH data, however, are subject to some limitations. The study examined, as others have done previously (Price et al, 2023), 4 variables related to healthrelated and QoL outcomes of switching from cigarette smoking to using ECs. The study did not assess patients with specific diseases such as cancer (Price et al, 2023), and additional, future studies would be required to ascertain whether switching improves fatigue, pain, emotional problems and QoL in those suffering from smokingrelated disease. A further limitation, and this arises due to the single, is the single, general question concerning QoL which was administered in the PATH study. Future studies could assess the impact of switching on more specific health status domains associated with QoL by administering more detailed instruments such as the 36item shortform health survey (SF-36) (Ware and Sherbourne, 1992) which along with many other domains also assesses those examined in this study, the US Centers for Disease Control and Prevention HealthRelated Quality of Life (HRQOL) instrument (Zack et al, 2004; Centers for Disease Control and Prevention, 2020), or the tobacco usespecific Tobacco Quality of Life Impact Tool (TQOLIT) (Ware et al, 2015) and the Smoking Cessation Quality of Life questionnaire (SCQoL) (Olufade et al, 1999; Shaw et al, 2001). Additionally, assessment of health status and QoL using instruments specific to known smoking related diseases such as COPD (van der Molen et al, 2003) may also be of interest, especially since smokers with COPD who switched to using ECs experienced improvements in 6MWD (Polosa et al, 2016; Polosa et al, 2018), a potential contributing factor to QoL in those suffering from COPD. To this point, singleitem measures may be lacking in reliability and validity when compared with diseasespecific instruments (Zhi et al, 2021).

In summary, smokers who quitted smoking or fully switched to using ECs had less healthrelated symptoms and better QoL than those who continued smoking. While the harm reduction potential of ECs is generally assessed by reductions in the risk of developing smokingrelated disease, this impact on QoL should also be taken into account when assessing their harm reduction potential. Furthermore, the development of practices to help smokers switch and improve their QoL also needs to be considered.

Abbreviation	Meaning
6MWD	6‑minute walk duration
BRR	Balanced repeated replicate
CI	95% confidence intervals
COPD	Chronic obstructive pulmonary disease
EC	E‑cigarette
HRQOL	Health‑Related Quality of Life
MD	Mean difference
PATH	Population Assessment of Tobacco and Health
QoL	Quality of Life
SCQoL	Smoking Cessation Quality of Life questionnaire
TQOLIT	Tobacco Quality of Life Impact Tool
WHOQOL‑BREF	Abbreviated version of the World Health Organization Quality of Life instrument

Consent for publication

No individual person’s data are reported in this paper.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the PATH survey data repository:
https://www.icpsr.umich.edu/web/NAHDAP/studies/36231/datadocumentation

Competing interests

Y.C., J.L., X.C., Y.X., F.Z., J.Z. and X.L. are employees of Shenzhen Smoore Technology Ltd, a manufacturer and distributor of e‑cigarette products. I.M.F. is an independent consultant who provides scientific and regulatory support to e‑cigarette and tobacco product manufacturers, including Smoore, and is a Scientific Advisory Board Member of Qnovia, LLC. X.Z. and X.S. declare that they have no competing interests.

Funding

This work was funded by Shenzhen Smoore Technology Ltd.

Authors’ contributions

Y.C., I.M.F. and X.L. researched data and drafted the manuscript. J.L. and X.C. carried out the acquisition of the data and edited the manuscript. Y.X., F.Z., J.Z., and X.L. designed the study and edited the manuscript. X.Z. and X.S. contributed to the discussion and reviewed the manuscript.

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Table 1. Sociodemographic Characteristics. Data are sociodemographic characteristics of exclusive cigarette smokers at baseline (Wave 1) of the PATH study.

	Overall N = 7,122
	N (%)	Weighted % (95% CI)
Gender
Male	3,673 (51.6)	54.6 (53.4, 55.7)
Female	3,449 (48.4)	45.4 (44.3, 46.6)
Age
18 to 24 years old	1,459 (20.5)	13.2 (12.3, 14.0)
25 to 44 years old	2,917 (41.0)	43.4 (42.1, 44.7)
45 or more years old	2,746 (38.6)	43.4 (42.0, 44.8)
Race
White alone	5,328 (74.8)	76.7 (75.4, 78.0)
Black alone	1,151 (16.2)	16.1 (15.0, 17.2)
Other	643 (9.0)	7.2 (6.5, 8.0)
Ethnicity
Hispanic	897 (12.6)	10.9 (10.2, 11.7)
Not Hispanic	6,225 (87.4)	89.1 (88.3, 89.8)
Education
Less than bachelor’s degree	6,352 (89.6)	89.1 (88.3, 90.0)
Bachelor's or advanced degree	736.0 (10.4)	10.9 (10.0, 11.7)
Household Income
Less than $50,000	5,091 (77.6)	75.6 (74.3, 76.9)
$50,000 or more	1,473 (22.4)	24.4 (23.1, 25.7)
Health Insurance Coverage
Yes	5,230 (74.0)	74.9 (73.5, 76.2)
No	1,837 (26.0)	25.1 (23.8, 26.5)
Visited Emergency Room
Yes	2,402 (33.8)	32.5 (31.1, 33.9)
No	4,708 (66.2)	67.5 (66.1, 68.9)

Table 2. Switching Behaviours. Data are unweighted counts, prevalence, and weighted prevalence of switching behaviours between Wave 2 and Wave 5 among adult exclusive cigarette smokers at baseline (Wave 1) of the PATH study.

	Wave 2 (N = 6,795)		Wave 3 (N = 5,132)		Wave 4 (N = 4,850)		Wave 5 (N = 4,681)
	N (%)	Weighted % (95% CI)	N (%)	Weighted % (95% CI)	N (%)	Weighted % (95% CI)	N (%)	Weighted % (95% CI)	P value
Switching behaviour									<.001
Full switching^a	114 (1.7)	1.6 (1.25, 1.95)	130 (2.5)	2.6 (2.15, 3.11)	129 (2.7)	2.6 (2.15, 3.12)	206 (4.0)	4.2 (3.60, 4.71)	<.001
Non‑switching^b	5,186 (76.3)	76.4 (75.19, 77.62)	3,635 (70.8)	70.7 (69.14, 72.27)	3,362 (69.3)	69.4 (67.68, 71.14)	2,874 (61.4)	61.8 (60.06, 63.56)	<.001
Partial switching^c	848 (12.5)	12.1 (11.17, 12.98)	581 (11.3)	11.2 (10.22, 12.16)	490 (10.1)	9.4 (8.44, 10.26)	591 (12.6)	11.6 (10.65, 12.61)	<.001
Quitting^d	647 (9.5)	9.9 (9.02, 10.80)	786 (15.3)	15.5 (14.24, 16.72)	869 (17.9)	18.6 (17.26, 19.95)	1,010 (21.6)	22.4 (20.80, 24.00)	<.001

^aAdult respondents who were current established smokers (who have smoked at least 100 cigarettes in their lifetime and currently smoke every day or some days without using any e‑cigarette products) at Wave 1 and fully switched to exclusive EC use in the subsequent waves.

^bAdult respondents who were current established smokers at Wave 1 and remained as smokers in the subsequent waves.

^cAdult respondents who were current established smokers at Wave 1 and switched to dual use of both cigarettes and ECs in the following waves.

^dAdult respondents who were current established smokers at Wave 1 and quit smoking in the following waves.

Table 3. Impact of Switching Behaviour on in Health‑Related Symptoms and QoL^*. Data are unadjusted and adjusted mean differences (95% CI) in scores for fatigue, pain, emotional problems and QoL associated with partial switching, full switching, and quitting, compared with non‑switching.

	Unadjusted		Adjusted^#
	Mean Difference (95% CI)	P value	Mean Difference (95% CI)	P value
Fatigue
Non‑switching	Ref.	Ref.	Ref.	Ref.
Partial switching	0.067 (0.020, 0.113)	0.0323	‑0.004 (‑0.040, 0.033)	0.843
Full switching	‑0.067 (‑0.171, 0.037)	0.5922	‑0.092 (‑0.167, ‑0.017)	0.016
Quitting	‑0.143 (‑0.196, ‑0.090)	<0.001	‑0.129 (‑0.165, ‑0.093)	<.001
Pain
Non‑switching	Ref.	Ref.	Ref.	Ref.
Partial switching	0.191 (0.043, 0.339)	0.062	0.078 (‑0.017, 0.174)	0.115
Full switching	‑0.464 (‑0.753, ‑0.175)	0.012	‑0.156 (‑0.351, 0.038)	0.108
Quitting	‑0.678 (‑0.854, ‑0.502)	<0.001	‑0.269 (‑0.364, ‑0.175)	<.001
Emotional Problems
Non‑switching	Ref.	Ref.	Ref.	Ref.
Partial switching	0.179 (0.116, 0.242)	<0.001	0.016 (‑0.027, 0.058)	0.470
Full switching	‑0.006 (‑0.153, 0.140)	0.999	‑0.089 (‑0.175, ‑0.002)	0.044
Quitting	‑0.165 (‑0.230, ‑0.100)	<0.001	‑0.151 (‑0.193, ‑0.109)	<.001
Quality of Life
Non‑switching	Ref.	Ref.	Ref.	Ref.
Partial switching	‑0.026 (‑0.079, 0.027)	0.771	‑0.025 (‑0.059, 0.008)	0.142
Full switching	‑0.305 (‑0.427, ‑0.183)	<0.001	‑0.124 (‑0.193, ‑0.056)	<.001
Quitting	‑0.333 (‑0.390, ‑0.276)	<0.001	‑0.187 (‑0.220, ‑0.154)	<.001

Note: ^*QoL is quality of life: lower score indicates better quality of life; ^#Adjustedmean differences were obtained from a mixed‑effects regression model after controlling for baseline score (pain, fatigue, emotional problems and QoL), age, gender, race, level of education, and time.

Competing interest reported. Y.C., J.L., X.C., Y.X., F.Z., J.Z. and X.L. are employees of Shenzhen Smoore Technology Ltd, a manufacturer and distributor of e cigarette products. IMF is an independent consultant who provides scientific and regulatory support to e cigarette and tobacco product manufacturers, including Smoore, and is a Scientific Advisory Board Member of Qnovia, LLC. X.Z. and X.S. declare that they have no competing interests.

The Effects of Smokers Switching Behaviour on Health-Related Symptom Burden and Quality of Life: Analysis of US Prospective Longitudinal Cohort Study Data

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Abstract

Background

Objective

Methods

Results

Conclusions

Figures

BACKGROUND

METHODS