Work and Non-Work Physical Activity Predict Real-Time Smoking Level and Urges in Young Adults

Nadell, Melanie J.; Mermelstein, Robin J.; Hedeker, Donald; Márquez, David X.

doi:10.1093/ntr/ntu244

Cited by 10 publications

(23 citation statements)

References 41 publications

(51 reference statements)

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“…Also, we hypothesize that one's perception of their health status might be affected by disease activity. There is an inverse relationship between smoking and physical activity 29 and smoking has variable effects on disease activity in patients with IBD. 30, 31 Covariates were also assessed for multicollinearity.…”

Section: Methodsmentioning

confidence: 99%

Exercise Decreases Risk of Future Active Disease in Patients with Inflammatory Bowel Disease in Remission

Jones

Kappelman

Martin

et al. 2015

Inflammatory Bowel Diseases

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Background Although exercise impacts quality of life in patients with inflammatory bowel disease (IBD), little is known about its role in disease activity. Among IBD patients in remission, we aimed to evaluate the association between exercise and subsequent active disease. Methods We performed a prospective study using the Crohn's and Colitis Foundation of America (CCFA) Partners Internet-based cohort of individuals with self-reported IBD. We identified participants in remission, defined as short Crohn's disease activity index (sCDAI) <150 or simple clinical colitis activity index (SCCAI) ≤2. The primary exposure was exercise status, measured using the validated Godin leisure time activity index. The primary study outcome, assessed after six months, was active disease defined using the above disease activity index thresholds. We used bivariate and multivariate analyses to describe the independent association between exercise and risk of active disease. Results We identified 1308 patients with Crohn's Disease (CD) and 549 with ulcerative or indeterminate colitis (UC/IC) in remission, of whom 227(17.4%) with CD and 135 (24.6%) with UC/IC developed active disease after 6 months. Higher exercise level was associated with decreased risk of active disease for CD (adjusted RR 0.72, 95% CI 0.55-0.94) and UC/IC (adjusted RR 0.78, 95% CI 0.54-1.13). Conclusions In patients with CD in remission, those with higher exercise levels were significantly less likely to develop active disease at six months. In patients with UC/IC in remission, patients with higher exercise levels were less likely to develop active disease at six months, however this was not statistically significant.

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Section: Methodsmentioning

confidence: 99%

Exercise Decreases Risk of Future Active Disease in Patients with Inflammatory Bowel Disease in Remission

Jones

Kappelman

Martin

et al. 2015

Inflammatory Bowel Diseases

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“…Nadell [ 21 ] found that higher weekly physical activity at work was associated with higher smoking behavior. A study by Willy showed that the more hours a smoking nurse aide worked per week, the less likely they were to stop smoking [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

The association between different types of physical activity and smoking behavior

Zhang,

Cao,

et al. 2023

BMC Psychiatry

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Background Smoking is harmful, which has become a major public health burden. Physical activity may be related to smoking. Physical activity is one of the current methods for smoking control and smoking cessation. Different types of physical activity may have different effect on smoking behavior. Objective The purpose of this study was to identify the direction and extent of the impact of different types of physical activity above moderate intensity (including work physical activity, recreational physical activity, commuter physical activity and sedentary behavior) on smoking behavior. Materials and methods In this study, a total of 2,015 individuals (1,233 males and 782 females, mean age 54.02±17.31 years) was selected from the representative population aged 20 and above in the National Health and Nutrition Survey of the United States from 2017 to 2018. Physical activity was assessed using the Global Physical Activity Questionnaire (GPAQ) ; the tobacco use questionnaire (SMQ) was used to determine whether the sample had smoking behavior at this stage. Binary Logistic regression analysis was performed with various physical activities as independent variables and smoking behavior as dependent variables. All data were analyzed through Statistical Product and Service Solutions (SPSS) 26.0. Results After adjusted for all confounding variables, physical activity at work was close to significantly associated with smoking behavior (P=0.053), odds ratio (OR) =1.135 (95%Cl: 0.999-1.289). Recreational physical activity was significantly associated with smoking behavior (P < 0.001), OR=0.729 (95%Cl: 0.639-0.832). Commuting physical activity was significantly associated with smoking behavior (P < 0.001), OR=1.214 (95%Cl:1.048-1.405). Sedentary behavior was significantly associated with smoking behavior (P < 0.001), OR=1.363 (95%Cl: 1.154-1.611). Conclusions Given that different types of physical activity have different associations with smoking behavior. Therefore, when physical activity is used as a tobacco control measurement, it is necessary to pay attention to the type and environment of physical activity. Recreational physical activities should be appropriately increased, sedentary behavior should be reduced, and smoking prohibit environment should be expanded as far as possible to achieve better clinical intervention effects.

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“…and 58.8% during the three 1st years of the 10-year period analyzed between 2008 and February 2010 (Biddle, Gorely & Marshall, 2009;Biddle et al, 2009aBiddle et al, , 2009bBiddle et al, , 2009cGorely et al, 2009aGorely et al, , 2009bHausenblas et al, 2008;McCormick et al, 2008McCormick et al, , 2009Rouse & Biddle, 2010 Hekler et al, 2012;Kim et al, 2014;Mata et al, 2012;Nadell et al, 2015;Thomas et al, 2011;Von Haaren et al, 2013;LePage & Crowther, 2010).…”

Section: Characteristics Of the Main Methodological Aspects About Emamentioning

confidence: 99%

mHealth technology for ecological momentary assessment in physical activity research: a systematic review

Zapata-Lamana

Lalanza

Losilla

et al. 2020

PeerJ

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Objective To systematically review the publications on ecological momentary assessment (EMA) relating to physical activity (PA) behavior in order to classify the methodologies, and to identify the main mHealth technology-based tools and procedures that have been applied during the first 10 years since the emergence of smartphones. As a result of this review, we want to ask if there is enough evidence to propose the use of the term “mEMA” (mobile-based EMA). Design A systematic review according to PRISMA Statement (PROSPERO registration: CRD42018088136). Method Four databases (PsycINFO, CINALH, Medline and Web of Science Core Collection) were searched electronically from 2008 to February 2018. Results A total of 76 studies from 297 potential articles on the use of EMA and PA were included in this review. It was found that 71% of studies specifically used “EMA” for assessing PA behaviors but the rest used other terminology that also adjusted to the inclusion criteria. Just over half (51.3%) of studies (39) used mHealth technology, mainly smartphones, for collecting EMA data. The majority (79.5%) of these studies (31 out of 39) were published during the last 4 years. On the other hand, 58.8% of studies that only used paper-and-pencil were published during the first 3 years of the 10-year period analyzed. An accelerometer was the main built-in sensor used for collecting PA behavior by means of mHealth (69%). Most of the studies were carried out on young-adult samples, with only three studies in older adults. Women were included in 60% of studies, and healthy people in 82%. The studies lasted between 1 and 7 days in 57.9%, and between three and seven assessments per day were carried out in 37%. The most popular topics evaluated together with PA were psychological state and social and environmental context. Conclusions We have classified the EMA methodologies used for assessing PA behaviors. A total of 71% of studies used the term “EMA” and 51.3% used mHealth technology. Accelerometers have been the main built-in sensor used for collecting PA. The change of trend in the use of tools for EMA in PA coincides with the technological advances of the last decade due to the emergence of smartphones and mHealth technology. There is enough evidence to use the term mEMA when mHealth technology is being used for monitoring real-time lifestyle behaviors in natural situations. We define mEMA as the use of mobile computing and communication technologies for the EMA of health and lifestyle behaviors. It is clear that the use of mHealth is increasing, but there is still a lot to be gained from taking advantage of all the capabilities of this technology in order to apply EMA to PA behavior. Thus, mEMA methodology can help in the monitoring of healthy lifestyles under both subjective and objective perspectives. The tendency for future research should be the automatic recognition of the PA of the user without interrupting their behavior. The ecological information could be completed with voice messages, image captures or brief text selections on the touch screen made in real time, all managed through smartphone apps. This methodology could be extended when EMA combined with mHealth are used to evaluate other lifestyle behaviors.

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Work and Non-Work Physical Activity Predict Real-Time Smoking Level and Urges in Young Adults

Cited by 10 publications

References 41 publications

Exercise Decreases Risk of Future Active Disease in Patients with Inflammatory Bowel Disease in Remission

Exercise Decreases Risk of Future Active Disease in Patients with Inflammatory Bowel Disease in Remission

The association between different types of physical activity and smoking behavior

mHealth technology for ecological momentary assessment in physical activity research: a systematic review

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