Cancer is one of the leading causes of morbidity and mortality worldwide and in the United States. 1 – 4 The American Cancer Society estimates that 1 in 3 men and women in the general population will develop some type of cancer during their lifetime, and 1 in 5 will die from cancer. 4 Smoking is
Baruch Vainshelboim, Zhongming Chen, Ricardo M. Lima and Jonathan Myers
Ray M. Merrill
altitude), as well as urban residency, poverty, tobacco smoking, and obesity, have been associated with physical activity. The influence of these variables on physical activity may be direct or indirect. Associations may also be modified by other variables such as gender. A direct effect of air temperature
Mohamad Al-Tannir, Samer Kobrosly, Taha Itani, Mariam El-Rajab and Sawsan Tannir
This survey aims to assess the prevalence of physical activity among adult Lebanese, and to report the relationship between sociodemographic variables and physical activity behavior, highlighting the correlates discouraging people to carry out physical activity.
A cross-sectional study using an anonymous self-reported questionnaire was conducted on 346 adults from four Lebanese districts. Demographic characteristics, physical activity, smoking status, alcohol consumption, and medical history were obtained.
Prevalence of physical activity among Lebanese adults was 55.5% (192/346). Age, BMI, marital status, medical history, occupation, educational level, and smoking were significantly associated with physical activity (P < .05). Inactive obese participants were about three times more likely to report hypertension and diabetes than inactive normal weight participants (P = .013). BMI was significantly higher among inactive participants (P = .014).
Physical activity among Lebanese adults was comparable to other populations. Married, non–office workers, and smokers were the main correlates of physical inactivity in Lebanese adulthood.
Pouya Saeedi, Mohd Nasir Mohd Taib and Hazizi Abu Saad
Nutritional supplement (NS) use has increased among the general population, athletes, and fitness club participants and has become a widespread and acceptable behavior. The objective of this study was to determine the differences in sociodemographic, health-related, and psychological factors between NS users and nonusers. A case-control study design was used, whereby participants included 147 NS users (cases) and 147 nonusers (controls) age 18 yr and above who exercised at least 3 d/wk in 24 fitness clubs in Tehran. A self-administered pretested and validated questionnaire was used to collect data. The results showed that on average, NS users were younger (29.8 ± 9.5 yr) than nonusers (35.5 ± 12.2 yr). Logistic-regression analysis showed that NS use was significantly associated with moderate or high physical activity level (PAL), smoking, gender, eating attitude, and age. In conclusion, NS users were more likely to be female, younger, and smokers; to have moderate or high PAL; and to be more prone to eating disorders than nonusers.
Richard R. Suminski, Larry T. Wier, Walker Poston, Brian Arenare, Anthony Randles and Andrew S. Jackson
Nonexercise models were developed to predict maximal oxygen consumption (VO2max). While these models are accurate, they don’t consider smoking, which negatively impacts measured VO2max. The purpose of this study was to examine the effects of smoking on both measured and predicted VO2max.
Indirect calorimetry was used to measure VO2max in 2,749 men and women. Physical activity using the NASA Physical Activity Status Scale (PASS), body mass index (BMI), and smoking (pack-y = packs·day * y of smoking) also were assessed. Pack-y groupings were Never (0 pack-y), Light (1–10), Moderate (11–20), and Heavy (>20). Multiple regression analysis was used to examine the effect of smoking on VO2max predicted by PASS, age, BMI, and gender.
Measured VO2max was significantly lower in the heavy smoking group compared with the other pack-y groups. The combined effects of PASS, age, BMI, and gender on measured VO2max were significant. With smoking in the model, the estimated effects on measured VO2max from Light, Moderate, and Heavy smoking were –0.83, –0.85, and –2.56 ml·kg−1·min−1, respectively (P < .05).
Given that 21% of American adults smoke and 12% of them are heavy smokers, it is recommended that smoking be considered when using nonexercise models to predict VO2max.
Paul D. Loprinzi and Jerome F. Walker
To our knowledge, no longitudinal epidemiological study among daily smokers has examined the effects of physical activity change/trajectory on smoking cessation. The purpose of this study was to examine the longitudinal effects of changes in physical activity on smoking cessation among a national sample of young (16–24 y) daily smokers.
Data from the 2003–2005 National Youth Smoking Cessation Survey were used (N = 1178). Using hierarchical agglomerative cluster analysis, 5 distinct self-reported physical activity trajectories over 3 time periods (baseline, 12-month, and 24-month follow-up) were observed, including stable low physical activity, decreasing physical activity, curvilinear physical activity, stable high physical activity, and increasing physical activity. Nicotine dependence (Heaviness of Smoking Index) and demographic parameters were assessed via survey.
With stable low physical activity (16.2% quit smoking) serving as the referent group, those in the stable high physical activity (24.8% quit smoking) group had 1.8 greater odds of not smoking at the 24-month follow-up period (odds ratio = 1.81; 95% confidence interval, 1.12–2.91) after adjusting for nicotine dependence, age, gender, race-ethnicity, and education.
Maintenance of regular physical activity among young daily smokers may help to facilitate smoking cessation.
Nowall Al-Sayegh, Saud Al-Obaidi and Mohammed Nadar
Grip strength assessment reflects on overall health of the musculoskeletal system and is a predictor of functional prognosis and mortality. The purpose of this study was: examine whether grip-strength and fatigue resistance are impaired in smokers, determine if smoking-related impairments (fatigue-index) can be predicted by demographic data, duration of smoking, packets smoked-per-day, and physical activity.
Maximum isometric grip strength (MIGS) of male smokers (n = 111) and nonsmokers (n = 66) was measured before/after induced fatigue using Jamar dynamometer at 5-handle positions. Fatigueindex was calculated based on percentage change in MIGS initially and after induced fatigue.
Number of repetitions to squeeze the soft rubber ball to induce fatigue was significantly lower in smokers compared with nonsmokers (t = 10.6, P < .001 dominant hand; t = 13.9, P < .001 nondominant), demonstrating a significantly higher fatigue-index for smokers than nonsmokers (t = –8.7, P < .001 dominant hand; t = –6.0, P < .001 nondominant). The effect of smoking status on MIGS scores was significantly different between smokers and nonsmokers after induced fatigue (β = –3.98, standard error = 0.59, P < .001) where smokers experienced on average a reduction of nearly 4 MIGS less than nonsmokers before fatigue. Smoking status was the strongest significant independent predictor of the fatigue-index.
Smokers demonstrated reduced grip strength and fast fatigability in comparison with nonsmokers.
Brad R. Julius, B. Ann Ward, James H. Stein, Patrick E. McBride, Michael C. Fiore, Timothy B. Baker, F. Javier Nieto and Lisa H. Colbert
We examined the association between ambulatory activity and biological markers of health in smokers.
Baseline data from 985 subjects enrolled in a pharmacologic smoking cessation trial were examined. Body size, blood pressure, total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), total and small LDL particles, LDL size, high density lipoprotein cholesterol, triglycerides (TG), C-reactive protein (CRP), creatinine, fasting glucose, and hemoglobin A1c were assessed in relation to pedometer-assessed ambulatory activity, as was the odds of metabolic syndrome and CRP > 3 mg/L. Effect modification by gender was examined.
Only waist circumference was lower with greater steps/day in the men and women combined (P trend < 0.001). No other significant relationships were noted in men, while women with ≥ 7500 steps/day had lower weight, BMI, CRP, TG, total, and small LDL particles compared with those with < 7500 steps/day. These women also had 62% and 43% lower odds of metabolic syndrome and elevated CRP, respectively, compared with the less active women. Adjustment for BMI attenuated all the associations seen in women.
Greater ambulatory activity is associated with lower levels of metabolic and cardiovascular risk factors in female smokers which may, in part, be mediated by a reduction in BMI.
This study examined the relationship between sport participation on the one hand and smoking and the use of alcohol and drugs on the other among Icelandic youth 12- to 15 years of age. Two indicators of sport participation were employed; one measured its extent in formally organized sports clubs, while the other measured the extent to which the subjects were involved in sports regardless of whether they trained informally or with a formally organized sports club. Two random samples of 12- to 15-year-olds from the urban areas of southwest Iceland, comprising 456 and 358 subjects, were analyzed to determine if there was a negative correlation between sport participation and the measures of deviant behavior in question. However, 3 of the 12 relationships tested were not significant at the .05 level. The findings do not change significantly when gender, social class, and age are controlled. It is concluded that the findings give cross-cultural support to previous research results indicating a negative relationship between youth, sport participation, and the use of alcohol, drugs, and smoking.
Jennifer L. Copeland
the importance of sedentary behavior as a risk factor for functional impairments that are especially relevant to older adults ( Dogra, Ashe, et al., 2017 ). Sitting Is Not the New Smoking The field of sedentary physiology is still in its infancy, especially in comparison with our understanding of the