Skip to main content
Download PDF

The association between different types of physical activity and smoking behavior

BMC Psychiatry volume 23, Article number: 927 (2023) Cite this article

Abstract

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.

Peer Review reports

Background

Smoking not only seriously harms physical and mental health, but also harms passive smokers, which has become one of the major public health problems. Even e-cigarettes have no small impact on health [1]. Smoking is one of the leading causes of preventable premature death worldwide, and according to a 2017 report by the World Health Organization (WHO), smoking kills more than 70,000 people each year [2]. However, about 21% of the world's population still smokes [3]. Commercially available cigarettes contain more than 7,000 chemicals, and their combustion creates potentially toxic substances in mainstream smoke, side-stream smoke, secondhand smoke, third-hand smoke, and discarded cigarette butts [4]. Smoking is associated with a number of fatal diseases and causes diseases of almost all organs of the body, including cancer, respiratory, cardiovascular, infectious and neurological diseases, leading to a decline in human health [5, 6]. Maternal smoking during pregnancy also affects fetal health and lung function [7]. In addition, both maternal smoking during pregnancy and paternal smoking were associated with overweight and obesity in adult daughters [8].

Adequate and appropriate physical activity enhances muscle and bone health, improves cardiovascular health, enhances immune system function, reduces anxiety, depression, and stress, and improves mood and well-being. Physical inactivity is a modifiable risk factor for cardiovascular disease and a variety of other chronic diseases, including diabetes, cancer, obesity, high blood pressure, bone and joint diseases, and anxiety and depression [9]. Anxiety and depression may lead to more smoking. At the same time, relevant studies have proved that physical activity is related to smoking behavior, and smokers tend to have less physical activity than non-smokers [10, 11], and exercise can quickly reduce the desire for cigarettes [12]. This may be related to the positive emotions that physical activity can produce, so physical activity is also currently used as a means of tobacco control. Given the dangers of smoking, the importance of physical activity to health, and the modifiable nature of physical activity and smoking behavior [13], it is important to explore the relationship between the two for effective tobacco control.

Although previous studies have confirmed the correlation between physical activity and smoking behavior, physical activity is not always beneficial and sometimes has negative effects, and inappropriate physical activity may cause damage to the body [14]. Kye [15] showed that high intensity physical activity at work was negatively correlated with obesity. Physical activity at work can have negative effects, while recreational physical activity in leisure time often leads to good emotional experiences [16]. Furthermore, physical activity is influenced by socio-demographic, biological, cognitive, emotional, sociocultural, and environmental factors [17]. Therefore, the intervention of physical activity on smoking behavior may not always be positive, and we suspect that different types of physical activity may have different associations with the effects of smoking behavior. Therefore, according to the different purpose of physical activity, this study divides it into four different types: work physical activity, recreational physical activity, commuting physical activity and sedentary behavior. The aim is to identify the direction and degree of correlation between different types of physical activity and smoking behavior, and put forward scientific targeted suggestions in daily physical activity, so as to control smoking more effectively to a certain extent.

Methods and materials

Object

The National Nutrition Examination Survey (NHANES) is a population-based, cross-sectional survey designed to collect information on the health and nutritional status of the U.S. household population [18]. This study used a representative sample of 2,015 individuals aged 20 years and older stratified by NHANES in 2017-2018. NHANES covers about 15,000 households, all of which are U.S. residents who have lived in the United States for at least two months. The survey protocol and secondary analyses of the data were approved by the Ethics Review Committee of the National Center for Health Statistics. All adult participants in NHANES gave informed consent to the purpose, risks and benefits of the study and signed an informed consent form [19]. Additional details on study design, sampling and exclusion criteria are shown in the figure below (See Fig. 1).

Fig. 1
figure 1

Data screening flow chart

Full size image

Physical activity assessment

All types of physical activity (work physical activity, recreational physical activity, commuting physical activity, and sedentary behavior) were assessed using the GPAQ. Whether they engage in more than moderate intensity work physical activity, recreational physical activity, and commuting physical activity during the week. Sedentary duration <600min or ≥600min in a 24-hour period. The codes "1" and "2" indicate whether this type of physical activity or sedentary duration <600min and ≥600min are in the final database, respectively.

Smoking behavior assessment

Smoking behavior data is extracted from the SMQ dateset, which provides survey participants' cigarette use history, age of start, use in the last 30 days, cigarette brand, sub-brand, and other relevant details. For adults 18 years of age or older, trained interviewers ask questions at home using a computer-assisted Personal Interview (CAPI) system. The codes "1" and "2" represent whether or not you smoke at the current stage.

Covariate

Covariates included gender, age, race, education, marital status, and income-poverty ratio. A total of 2,015 participants were divided into three age groups: 20-39 years, 40-59 years, and >60 years. Race is divided into Hispanic, non-Hispanic white, non-Hispanic black, non-Hispanic Asian, and other races. The education level is divided into below high school, high school and above high school. Marital status was divided into cohabitation, married living alone (widowed, divorced, separated) and never married. The poverty ratio is a measure of poverty measured by dividing household income by the survey year. In this study, the poverty ratio was used to create two income conditions, poor (<1.3) and middle income (≥1.3) [20].

Statistical analysis

We used Microsoft Excel 2010 to extract and merge the raw data and exclude missing and useless (rejected, don't know) items. The database includes adults 20 years of age and older with complete information. For the purpose of this study, we tested the significance of the differences in covariates between the "smoking" and "non-smoking" groups. Rank sum test was used for quantitative variables and chi-square test for categorical variables. We used a binary logistic regression model to analyze the relationship between different types of physical activity and smoking behavior. All data were analyzed using the Statistical Product and Service Solutions (SPSS) version 26.0, and a P-value less than 0.05 was considered statistically significant (bilateral test). Variables that were statistically significant in the univariate analysis were included in the stepwise binary logistic regression analysis. In univariate analysis, all covariables (P < 0.05) except gender (P=0.077) were statistically significant. In the significance test of measurement data, age P < 0.05 (variance was not homogeneous), P(bilateral) < 0.001, the difference was not statistically significant. Therefore, age and sex were not excluded as confounding factors in logistic regression analysis. A-entry=0.05 and a-exit=0.10 were used to select and exclude confounding variables.

When analyzing the relationship between physical activity at work and smoking behavior. We took work physical activity as the independent variable (1=yes, 2=no) and smoking (1=smoking, 2=no smoking behavior) as the dependent variable. To exclude the effect of confounding variables, we built the following models: Model I: Only the independent variable work physical activity was adjusted. Model II: Adjusted for independent variables in model I plus demographic variables (race, education, marital status, income-poverty ratio). Model III: Adjusted for model II plus variables for recreational physical activity, commuting physical activity, and sedentary behavior.

When analyzing the relationship between recreational physical activity and smoking behavior. We took recreational physical activity as the independent variable (1=yes, 2=no) and smoking (1=smoking, 2=no smoking behavior) as the dependent variable. To exclude the effect of confounding variables, we built the following models: Model IV: Only the independent variable recreational physical activity was adjusted. Model V: Adjusted for independent variables in model IV plus demographic variables (race, education, marital status, income-poverty ratio). Model VI: Adjusted for model V plus variables for work physical activity, commuting physical activity, and sedentary behavior.

When analyzing the relationship between commuting physical activity and smoking behavior. We took commuting physical activity as the independent variable (1=yes, 2=no) and smoking (1=smoking, 2=no smoking behavior) as the dependent variable. To exclude the effect of confounding variables, we built the following models: Model VII: Only the independent variable commuting physical activity was adjusted. Model VIII: Adjusted for independent variables in model VII plus demographic variables (race, education, marital status, income-poverty ratio). Model IX: Adjusted for model VIII plus variables for work physical activity, recreational physical activity, and sedentary behavior.

On the relationship between sedentary behavior and smoking behavior. We took sedentary behavior as the independent variable (1=yes, 2=no) and smoking (1=smoking, 2=no smoking) as the dependent variable. To exclude the effect of confounding variables, we built the following model: Model X: Only the sedentary behavior of the independent variable was adjusted. Model XI: Adjusted for independent variables in model X plus demographic variables (race, education, marital status, income-poverty ratio). Model XII: Adjusted for model XI plus variables for work physical activity, recreational physical activity, and commuting physical activity.

Results

Demographic characteristics

The study included 2,015 adults aged 20 years or older in the 2017-2018 U.S. National Nutrition Examination Survey cycle who completed data on physical activity, smoking, and other demographic information. There were statistically significant differences in covariates and independent variables such as race, educational level, marital status and income poverty ratio between the smoking group and the non-smoking group (See Table 1).

Table 1 Demographic characteristics of adults aged 20 years and older, by smoking behavior
Full size table

Association between physical activity at work and smoking behavior

In logistic regression analysis, model I (without adjusting any confounding variables) showed an odds ratio (OR) of 1.396 (95%Cl:1.245-1.566) for the association between work physical activity and smoking behavior. Model II (adjusted for variables of gender, race, education, marital status, and income-poverty ratio) shows that OR=1.143 (95%Cl:1.009-1.296). Model III (adjusted for all confounding variables) shows OR=1.135 (95%Cl:0.999-1.289). The findings suggest that after adjusting for all confounding factors, physical activity at work is close to significant with smoking behavior, and physical activity at work may be a potential risk factor for smoking behavior. Weekly physical activity at work was associated with a 28.9 percent increased risk of smoking (P < 0.01) (See Table 2).

Table 2 Logistic regression analysis of physical activity at work and smoking behavior
Full size table

Association between recreational physical activity and smoking behavior

In logistic regression analysis, Model IV (without adjusting any confounding variables) showed that the odds ratio (OR) of the association between recreational physical activity and smoking behavior was 0.828 (95%Cl:0.737-0.931). Model V (adjusted for variables of gender, race, education, marital status, and income-poverty ratio) shows that OR=0.729 (95%Cl:0.639-0.832). Model VI (adjusted for all confounding variables) shows OR=0.695 (95%Cl:0.608-0.795). The findings showed that recreational physical activity was a protective factor for smoking behavior after adjusting for all confounding factors. Weekly recreational physical activity was associated with a 39.2-20.5% lower risk of smoking behavior (P < 0.01) (See Table 3).

Table 3 Logistic regression analysis of recreational physical activity and smoking behavior
Full size table

Association between commuting physical activity

In logistic regression analysis, Model VII (without adjusting any confounding variables) showed an odds ratio (OR) of 1.550 (95%Cl:1.355-1.773) for the association between commuting physical activity and smoking behavior. Model VIII (adjusted for variables of gender, race, education, marital status, and income-poverty ratio) shows that OR=1.214 (95%Cl:1.048-1.405). Model IX (adjusted for all confounding variables) shows OR=1.278 (95%Cl:1.101-1.484). The findings showed that after adjusting for all confounding factors, commuting physical activity was a risk factor for smoking behavior. Weekly commuting physical activity was associated with an increased risk of smoking by 10.1-48.4% (P < 0.01) (See Table 4).

Table 4 Logistic regression analysis of commuting physical activity and smoking behavior
Full size table

Association between sedentary behavior and smoking behavior

In logistic regression analysis, model X (without adjusting any confounding variables) showed that the odds ratio (OR) associated sedentary behavior with smoking behavior was 1.479 (95%Cl:1.265-1.729). Model XI (adjusted for variables of gender, race, education, marital status, and income-poverty ratio) shows that OR=1.363 (95%Cl:1.154-1.611). Model XII (adjusted for all confounding variables) shows that OR=1.319 (95%Cl:1.113-1.564). The results showed that after adjusting for all confounding factors, sedentary behavior ≥600min was a risk factor for smoking behavior. Sedentary behavior ≥600 minutes per day was associated with an 11.3-56.4% increased risk of smoking behavior (P < 0.01) (See Table 5).

Table 5 Logistic regression analysis of sedentary behavior and smoking behavior
Full size table

Discussion

In this study, we found that different types of physical activity were independently associated with smoking behavior in adults over 20 years of age. Work physical activity, commuting physical activity, and sedentary behavior might increase the risk of smoking behavior, and recreational physical activity may potentially decrease the risk of smoking behavior. Therefore, we will discuss "Work physical activity and smoking behavior," "Recreational physical activity and smoking behavior," "Commuting physical activity and smoking behavior," and "Sedentary behavior and smoking behavior," respectively, in the following texts.

Work physical activity and smoking behavior

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]. Our findings suggest that physical activity at work is a potential risk factor for smoking behavior and may increase the risk of smoking behavior by about 13.5%. Sports motivation may explain this problem in one way. Traditionally, physical activity is motivated by socializing and improving physical health and appearance. However, physical activity at work is not motivated by avoiding negative health problems, combating smoking, or improving physical appearance; it may be done out of necessity or compulsion [23]. Active natural physical exercise is associated with positive mood and fewer daily stressors, leading to lower depression scores [24]. Engaging in inactive physical activity at work can make your mood and mood worse [21]. Higher negative emotions were associated with increased smoking behavior [25]. In addition, engaging in non-active work physical activity may increase the risk of sitting and obesity, and at the same time, may not have more energy for exercise [26], which may also be associated with increased smoking behaviors.

Recreational physical activity and smoking behavior

In previous studies, Patel [27] has suggested that smokers tend to be less physically active or thinner. Holmen [28] has shown that the frequency of physical exercise is negatively correlated with smoking behavior, and smokers are more likely not to participate in exercise. Conway [29] has also reported that smoking is associated with lower exercise levels and lower physical endurance. This study supports the conclusion of previous studies that recreational physical activity is a protective factor for smoking behavior, reducing the risk of smoking behavior by about 30.5%. Studies have shown that moderate-intensity exercise is effective in reducing cravings for reward components, thereby delaying cravings for the anticipated reward or snack of smoking [30, 12]. Regular physical exercise before quitting smoking can reduce the occurrence of smoking behavior and put smokers in a favorable state to quit smoking [31]. People who regularly engaged in recreational physical activity may be more likely to experience the positive effects of exercise on their health [32], and they may place more emphasis on their health and thus resist smoking behaviors. Smoking can adversely affect pulmonary functions and endurance quality [33], which can reduce the performance of smokers and make them more likely to feel tired during exercise, leading to a decrease in physical activity among smokers. In addition, engaging in recreational physical activity can make the body release endorphins and dopamine, which can make people have a positive emotional experience, which may also be one of the reasons for reducing smoking behavior.

Commuting physical activity and smoking behavior

Commuting physical activity and smoking may have little been mentioned in previous studies, with a 2010 study showing no significant correlation between commuting activity and smoking [34]. Our findings may be somewhat different, suggesting that commuting to physical activity increases the risk of smoking behavior. Studies have shown that a majority of people in Italy support the introduction of a smoking ban in cars, especially in cars carrying children [35]. In some parts of the United States, smoke-free vehicle laws have also been enacted to protect the physical health of young people [36]. With the implementation of these laws, since smoking is prohibited in cars, smokers may smoke while walking or riding bicycles, or choose to walk and ride bicycles for the sake of smoking. At the same time, when walking and riding a bicycle, there is no legal constraint, which will create an environment that is convenient for smoking, which will make people more prone to smoking. Therefore, if you want to quit smoking or control smoking behavior, you should try to avoid creating an environment where you can smoke.

Sedentary behavior and smoking behavior

In the analysis of sedentary behavior and smoking behavior, our results differ from the study by Vanessa, which found no difference in sedentary behavior between smokers and non-smokers. Our findings support studies by Efendi [10] and Lee [11], which show that smokers tend to be less physically active and engage in more sedentary behavior. At the same time, sedentary behavior is significantly associated with mental illness, and prolonged sitting increases the risk of anxiety, depression, and suicide [37]. While another study has shown that for smokers, smoking can bring many perceived benefits, including enhanced mood, reduced anxiety, and weight control [38]. The negative effects of sedentary behavior may induce some people to smoke for relief. People who are regularly physically active are more confident in their ability to control their smoking, while people who have taken action to change their smoking behavior are more confident in their ability to exercise [39]. This may enable people with relatively short periods of sedentary behavior to control their smoking behavior more. Although sedentary behavior is less harmful than smoking [40], sedentary behavior can lead to smoking behavior, and smoking has a significant additive effect with low levels of physical activity [41], so it is necessary to avoid prolonged sedentary time.

Limitations and perspectives of this study

This study is innovative and significant to some extent, but has the following limitations: 1) We are not perfect in excluding confounding factors: The causes of smoking behavior are multi-factorial, including a variety of genetic, biological, environmental and social factors, and this study could not exclude all influencing factors.

Future research should, in our opinion, address the aforementioned issues. To account for additional confounding variables, it is advisable to include as many covariates as possible. Furthermore, even though we have classified physical activity, it is a complex behavioral activity that is influenced by many variables. Therefore, if the evaluation of physical activity could be more precise, we believe that this study could have significant implications for future research.

Conclusions

After adjusting for all confounding factors, physical activity at work was a potential risk factor for smoking behavior. Recreational physical activity was a protective factor for smoking behavior. Commuting physical activity and sedentary behavior are risk factors for smoking behavior. There is a strong association between physical activity and smoking behavior, but different types of physical activity have different associations with smoking behavior. Therefore, when physical activity is used for tobacco control, it cannot be confused, and 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.

Availability of data and materials

The datasets generated and/or analyzed during the current study are available in the [NHANES] repository, [NHANES Questionnaires, Datasets, and Related Documentation (cdc.gov)]. Raw data supporting the obtained results are available at the corresponding author.

Abbreviations

NHANES:

National Health and Nutritional Examination Survey

SPSS:

Statistical Product and Service Solutions

WHO:

World Health Organization

GPAQ:

Global Physical Activity Questionnaire

SMQ:

Smoking-Cigarette Use Questionnaire

OR:

Odds Ratio

CI:

Confidence Interval

P:

P-Value

CAPI:

Computer-Assisted Personal Interviewing

References

  1. Dinardo P, Rome ES. Vaping: the new wave of nicotine addiction. Cleve Clin J Med. 2019;86(12):789–98. https://doi.org/10.3949/ccjm.86a.19118.

    Article  PubMed  Google Scholar 

  2. Kim J, Song H, Lee J, Kim YJ, Chung HS, Yu JM, et al. Smoking and passive smoking increases mortality through mediation effect of cadmium exposure in the United States. Sci Rep. 2023;13(1):3878. https://doi.org/10.1038/s41598-023-30988-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Kaufman AR, Twesten JE, Suls J, McCaul KD, Ostroff JS, Ferrer RA, et al. Measuring Cigarette Smoking Risk Perceptions. Nicotine Tob Res. 2020;22(11):1937–45. https://doi.org/10.1093/ntr/ntz213.

    Article  PubMed  Google Scholar 

  4. Soleimani F, Dobaradaran S, De-la-Torre GE, Schmidt TC, Saeedi R. Content of toxic components of cigarette, cigarette smoke vs cigarette butts: A comprehensive systematic review. Sci Total Environ. 2022;813:152667. https://doi.org/10.1016/j.scitotenv.2021.152667. (Epub 2021 Dec 25).

    Article  CAS  PubMed  Google Scholar 

  5. Peterson LA, Hecht SS. Tobacco, e-cigarettes, and child health. Curr Opin Pediatr. 2017;29(2):225–30. https://doi.org/10.1097/MOP.0000000000000456.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Taucher E, Mykoliuk I, Lindenmann J, Smolle-Juettner FM. Implications of the immune landscape in COPD and lung cancer: smoking versus other causes. Front Immunol. 2022;21(13):846605. https://doi.org/10.3389/fimmu.2022.846605.

    Article  CAS  Google Scholar 

  7. McEvoy CT, Spindel ER. Pulmonary effects of maternal smoking on the fetus and child: effects on lung development, respiratory morbidities, and life long lung health. Paediatr Respir Rev. 2017;21:27–33. https://doi.org/10.1016/j.prrv.2016.08.005. (Epub 2016 Aug 19).

    Article  PubMed  Google Scholar 

  8. Harris HR, Willett WC, Michels KB. Parental smoking during pregnancy and risk of overweight and obesity in the daughter. Int J Obes (Lond). 2013;37(10):1356–63. https://doi.org/10.1038/ijo.2013.101. (Epub 2013 May 29).

    Article  CAS  PubMed  Google Scholar 

  9. Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. CMAJ. 2006;174(6):801–9. https://doi.org/10.1503/cmaj.051351.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Efendi V, Özalevli S, Naz İ, Kılınç O. The effects of smoking on body composition, pulmonary function, physical activity and health-related quality of life among healthy women. Tuberk Toraks. 2018;66(2):101–8. https://doi.org/10.5578/tt.50724. (English).

    Article  PubMed  Google Scholar 

  11. Lee B, Yi Y. Smoking, physical activity, and eating habits among adolescents. West J Nurs Res. 2016;38(1):27–42. https://doi.org/10.1177/0193945914544335. (Epub 2014 Jul 30).

    Article  PubMed  Google Scholar 

  12. Oh H, Taylor AH. Self-regulating smoking and snacking through physical activity. Health Psychol. 2014;33(4):349–59. https://doi.org/10.1037/a0032423. (Epub 2013 May 13).

    Article  PubMed  Google Scholar 

  13. Seet V, Abdin E, Asharani PV, Lee YY, Roystonn K, Wang P, et al. Physical activity, sedentary behaviour and smoking status among psychiatric patients in Singapore - a cross-sectional study. BMC Psychiatry. 2021;21(1):110. https://doi.org/10.1186/s12888-021-03103-7.

    Article  PubMed  PubMed Central  Google Scholar 

  14. O’Keefe JH, Patil HR, Lavie CJ, Magalski A, Vogel RA, McCullough PA. Potential adverse cardiovascular effects from excessive endurance exercise. Mayo Clin Proc. 2012;87(6):587–95. https://doi.org/10.1016/j.mayocp.2012.04.005.Erratum.In:MayoClinProc.2012Jul;87(7):704.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kye SY, Cho H, Thao TTP, Oh JK, Lim MK. Associations of physical activity at work and household income with obesity: a cross-sectional study among rural adults in Korea. Epidemiol Health. 2021;43:e2021003. https://doi.org/10.4178/epih.e2021003. (Epub 2020 Dec 29).

    Article  PubMed  Google Scholar 

  16. Hajo S, Reed JL, Hans H, Tulloch HE, Reid RD, Prince SA. Physical activity, sedentary time and sleep and associations with mood states, shift work disorder and absenteeism among nurses: an analysis of the cross-sectional Champlain Nurses’ Study. PeerJ. 2020;2(8):e8464. https://doi.org/10.7717/peerj.8464.

    Article  Google Scholar 

  17. Riebe D, Franklin BA, Thompson PD, Garber CE, Whitfield GP, Magal M, et al. Updating ACSM’s Recommendations for Exercise Preparticipation Health Screening. Med Sci Sports Exerc. 2015;47(11):2473–9. https://doi.org/10.1249/MSS.0000000000000664. (Erratum.In:MedSciSportsExerc.2016Mar;48(3):579).

    Article  CAS  PubMed  Google Scholar 

  18. Cao C, Liu Q, Yang L, Zheng X, Lan P, Koyanagi A, et al. Handgrip strength is associated with suicidal thoughts in men: Cross-sectional analyses from NHANES. Scand J Med Sci Spor. 2020;30:92–9. https://doi.org/10.1111/sms.13559.

    Article  Google Scholar 

  19. Yang L, Cao C, Kantor ED, Nguyen LH, Zheng X, Park Y, et al. Trends in sedentary behavior among the US population, 2001–2016. JAMA. 2019;321:1587–97. https://doi.org/10.1001/jama.2019.3636.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Fadeyev K, Nagao-Sato S, Reicks M. Nutrient and Food Group Intakes among U.S. Children (2–5 Years) Differ by Family Income to Poverty Ratio, NHANES 2011–2018. Int J Environ Res Public Health. 2021;18(22):11938. https://doi.org/10.3390/ijerph182211938.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Nadell MJ, Mermelstein RJ, Hedeker D, Marquez DX. Work and non-work physical activity predict real-time smoking level and urges in young adults. Nicotine Tob Res. 2015;17(7):803–9. https://doi.org/10.1093/ntr/ntu244. (Epub 2014 Nov 10).

    Article  PubMed  Google Scholar 

  22. Eriksen W. Work factors and smoking cessation in nurses’ aides: a prospective cohort study. BMC Public Health. 2005;27(5):142. https://doi.org/10.1186/1471-2458-5-142.

    Article  Google Scholar 

  23. Egli T, Bland HW, Melton BF, Czech DR. Influence of age, sex, and race on college students’ exercise motivation of physical activity. J Am Coll Health. 2011;59(5):399–406. https://doi.org/10.1080/07448481.2010.513074.

    Article  PubMed  Google Scholar 

  24. Steptoe A, Kimbell J, Basford P. Exercise and the experience and appraisal of daily stressors: a naturalistic study. J Behav Med. 1998;21(4):363–74. https://doi.org/10.1023/a:1018778730309.

    Article  CAS  PubMed  Google Scholar 

  25. McKercher CM, Schmidt MD, Sanderson KA, Patton GC, Dwyer T, Venn AJ. Physical activity and depression in young adults. Am J Prev Med. 2009;36(2):161–4. https://doi.org/10.1016/j.amepre.2008.09.036. (Epub 2008 Dec 5).

    Article  PubMed  Google Scholar 

  26. Ross A, Yang L, Wehrlen L, Perez A, Farmer N, Bevans M. Nurses and health-promoting self-care: do we practice what we preach? J Nurs Manag. 2019;27(3):599–608. https://doi.org/10.1111/jonm.12718. (Epub 2018 Oct 31).

    Article  PubMed  Google Scholar 

  27. Patel AV, Carter BD, Stevens VL, Gaudet MM, Campbell PT, Gapstur SM. The relationship between physical activity, obesity, and lung cancer risk by smoking status in a large prospective cohort of US adults. Cancer Causes Control. 2017;28(12):1357–68. https://doi.org/10.1007/s10552-017-0949-0. (Epub 2017 Sep 22).

    Article  PubMed  Google Scholar 

  28. Holmen TL, Barrett-Connor E, Clausen J, Holmen J, Bjermer L. Physical exercise, sports, and lung function in smoking versus nonsmoking adolescents. Eur Respir J. 2002;19(1):8–15. https://doi.org/10.1183/09031936.02.00203502. (Erratum.In:EurRespirJ2002Mar;19(3):585).

    Article  CAS  PubMed  Google Scholar 

  29. Conway TL, Cronan TA. Smoking, exercise, and physical fitness. Prev Med. 1992;21(6):723–34. https://doi.org/10.1016/0091-7435(92)90079-w.

    Article  CAS  PubMed  Google Scholar 

  30. Kurti AN, Dallery J. Effects of exercise on craving and cigarette smoking in the human laboratory. Addict Behav. 2014;39(6):1131–7. https://doi.org/10.1016/j.addbeh.2014.03.004. (Epub 2014 Mar 13).

    Article  PubMed  Google Scholar 

  31. De Jesus S, Prapavessis H. Smoking behaviour and sensations during the pre-quit period of an exercise-aided smoking cessation intervention. Addict Behav. 2018;81:143–9. https://doi.org/10.1016/j.addbeh.2018.01.035. (Epub 2018 Feb 22).

    Article  PubMed  Google Scholar 

  32. Frisk J, Brynhildsen J, Ivarsson T, Persson P, Hammar M. Exercise and smoking habits among Swedish postmenopausal women. Br J Sports Med. 1997;31(3):217–23. https://doi.org/10.1136/bjsm.31.3.217.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Louie D. The effects of cigarette smoking on cardiopulmonary function and exercise tolerance in teenagers. Can Respir J. 2001;8(4):289–91. https://doi.org/10.1155/2001/701384.

    Article  CAS  PubMed  Google Scholar 

  34. Kwaśniewska M, Kaczmarczyk-Chałas K, Pikala M, Broda, Kozakiewicz K, Pajak A, Tykarski A, et al. Socio-demographic and lifestyle correlates of commuting activity in Poland. Prev Med. 2010;50(5–6):257–61. https://doi.org/10.1016/j.ypmed.2010.02.011. Epub 2010 Feb 26.

    Article  PubMed  Google Scholar 

  35. Martínez-Sánchez JM, Gallus S, Lugo A, Fernández E, Invernizzi G, Colombo P, et al. Smoking while driving and public support for car smoking bans in Italy. Tob Control. 2014;23(3):238–43. https://doi.org/10.1136/tobaccocontrol-2012-050700. (Epub 2012 Dec 21).

    Article  PubMed  Google Scholar 

  36. Patel M, Thai CL, Meng YY, Kuo T, Zheng H, Dietsch B, et al. Smoke-free car legislation and student exposure to smoking. Pediatrics. 2018;141(Suppl 1):S40–50. https://doi.org/10.1542/peds.2017-1026H.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Jiang L, Cao Y, Ni S, Chen X, Shen M, Lv H, et al. Association of sedentary behavior with anxiety, depression, and suicide ideation in college students. Front Psychiatry. 2020;11(11):566098. https://doi.org/10.3389/fpsyt.2020.566098.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Nair US, Collins BN, Napolitano MA. Differential effects of a body image exposure session on smoking urge between physically active and sedentary female smokers. Psychol Addict Behav. 2013;27(1):322–7. https://doi.org/10.1037/a0031367. (Epub 2012 Dec 31).

    Article  PubMed  Google Scholar 

  39. King TK, Marcus BH, Pinto BM, Emmons KM, Abrams DB. Cognitive-behavioral mediators of changing multiple behaviors: smoking and a sedentary lifestyle. Prev Med. 1996;25(6):684–91. https://doi.org/10.1006/pmed.1996.0107.

    Article  CAS  PubMed  Google Scholar 

  40. Vallance JK, Gardiner PA, Lynch BM, D’Silva A, Boyle T, Taylor LM, et al. Evaluating the evidence on sitting, smoking, and health: is sitting really the new smoking? Am J Public Health. 2018;108(11):1478–82. https://doi.org/10.2105/AJPH.2018.304649. (Epub 2018 Sep 25).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Jackson SE, Brown J, Ussher M, Shahab L, Steptoe A, Smith L. Combined health risks of cigarette smoking and low levels of physical activity: a prospective cohort study in England with 12-year follow-up. BMJ Open. 2019;9(11):e032852. https://doi.org/10.1136/bmjopen-2019-032852.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

We would like to thank all the staff and participants of the National Health and Nutrition Examination Survey 2017-2018 cycles for their valuable contributions. Any interpretation or conclusion related to this manuscript does not represent the views of the NHANES. We would also like to thank the editors and reviewers for their valuable and constructive comments to help us improve the manuscript. And we especially thank Dr. J.H. for his constructive comments.

Funding

This study were supported by the 2019 Sports Research Project of Henan Province Sports Bureau (Grants No. 2019052) and the 2020 General Project of Henan Province Education Science "13th Five-Year Plan" (Grants No. 2020YB0014).

Author information

Authors and Affiliations

  1. School of Physical Education (Main Campus), Zhengzhou University, Zhengzhou, Henan, P.R. China

    Jipeng Zhang, Yiwen Cao, Hongfei Mo & Rui Feng

  2. College of Public Health, Zhengzhou University, Zhengzhou, Henan, P. R. China

    Hongfei Mo

Authors
  1. Jipeng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yiwen Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hongfei Mo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rui Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.Z. conceived and designed the study. J.Z. organized the database, performed the statistical analysis and wrote the manuscript. Y.C. and H.M. confirmed the accuracy of the written language. J.Z., H.M. and R.F. revised the manuscript. All authors edited, revised, and certified the final version of this manuscript.

Corresponding authors

Correspondence to Hongfei Mo or Rui Feng.

Ethics declarations

Ethics approval and consent to participate

All procedures performed in the study were in accordance with the Declaration of Helsinki. The study protocols for NHANES were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board (Protocol#2017–1). All adult participants in NHANES had provide informed consent to the purpose, risks and benefits of the study and signed an informed consent form.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, J., Cao, Y., Mo, H. et al. The association between different types of physical activity and smoking behavior. BMC Psychiatry 23, 927 (2023). https://doi.org/10.1186/s12888-023-05416-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12888-023-05416-1

Keywords

BMC Psychiatry

ISSN: 1471-244X

Contact us