Increased 24-hour energy expenditure in cigarette smokers.

Hofstetter, Angela

doi:10.1097/00006534-198678060-00093

Cited by 65 publications

(88 citation statements)

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“…The results are in accordance with evidence that former smokers show the highest and current smokers the lowest proportion of Smoking and overweight U John et al overweight and obesity. [1][2][3][4]6,7 The results are consistent with the evidence that revealed an increased energy expenditure from smoking [13][14][15][16][17] and from nicotine supply both in humans and animals. 12,18 Furthermore, the findings confirm evidence about the relation between number of cpd and body weight among former smokers.…”

Section: Smoking and Overweight U John Et Alsupporting

confidence: 85%

“…12 Evidence revealed an increase of energy expenditure while smoking, both in resting and in light physical activity conditions. [13][14][15][16][17] Nicotine supplied by patch after smoking cessation decreased caloric intake in a dose-related manner. 18 According to an animal study nicotine may lengthen intermeal time and simultaneously decrease the size of the meals taken.…”

Section: Introductionmentioning

confidence: 99%

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Smoking status, cigarettes per day, and their relationship to overweight and obesity among former and current smokers in a national adult general population sample

et al. 2005

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BACKGROUND: Weight gain after smoking cessation is perceived to be a barrier against quitting smoking. The goal was to analyze overweight and obesity depending on smoking status and number of cigarettes per day (cpd) among former and current smokers. METHODS: The sample included 7124 residents of Germany aged 18-79 y from a national health examination survey (participation rate: 61.4%). Body weight and height were objectively measured; smoking status and cpd were assessed by a questionnaire administered in a health examination center. RESULTS: The number of cpd was positively related to being overweight and more so to obesity among former smoking men, but not women. The results were adjusted for age, school education, exercise and alcohol consumption. Men who formerly had smoked more than 30 cpd had an adjusted odds ratio (OR) of 5.0 for obesity compared to men who had never smoked. CONCLUSION: With an increasing number of cpd more psychological and physiological processes of compensation of nicotine supply after smoking cessation may be expected. Male smokers should be provided with information on how to prevent weight gain after smoking cessation. To foster smoking cessation, female smokers should be informed that women who stop smoking manage to have no increase in the rates of overweight or obesity when considered at the general population level.

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Section: Smoking and Overweight U John Et Alsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Smoking status, cigarettes per day, and their relationship to overweight and obesity among former and current smokers in a national adult general population sample

et al. 2005

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“…Results for chronic influences of smoking on RMR, however, are contradictory. Hofstetter et al (1986) and Warwick and Busby (1993) showed that smoking of many cigarettes spread over the whole day increases energy expenditure for several hours because of an additive effect. This could be the reason that in our study, in addition to body composition smoking status was a significant predictor of RMR only in the elderly men as they were smoking more cigarettes per day than subjects of the other study groups (data not shown).…”

Section: Discussionmentioning

confidence: 99%

“…Despite the significant differences we observed in PAL between young and elderly subjects, these were very small (elderly vs younger women: 1.69 vs 1.64; elderly vs younger men: 1.66 vs 1.70) and PAL was not a significant predictor of RMR in our subjects. The influence of FM, body fat distribution, PAL and smoking on RMR has been discussed in detail elsewhere (Hofstetter et al, 1986;Weststrate et al, 1990;Moffat & Owens, 1991;Leenen et al, 1992;Nelson et al, 1992;Svendsen et al, 1993;Pannemans & Westerterp, 1995;Ryan et al, 1996;Withers et al, 1998;Nielsen et al, 2000;Kimm et al, 2001;Lührmann et al, 2001).…”

Section: Discussionmentioning

confidence: 99%

Lower resting metabolic rate in the elderly may not be entirely due to changes in body composition

et al. 2004

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Objective: To investigate whether or not the lower resting metabolic rate (RMR) in the elderly is entirely due to changes in body composition. Design: Cross-sectional data of 132 female (age 69.975.5 y, body mass index (BMI) 26.574.0 kg/m 2 ) and 84 male (age 68.975.1 y, BMI 26.172.8 kg/m 2 ) participants of the longitudinal study on nutrition and health status in an aging population of Giessen, Germany, as well as that of 159 young women (age 24.873.0 y, BMI 21.172.5 kg/m 2 ) and 67 young men (age 26.873.4 y, BMI 23.372.4 kg/m 2 ) were analysed. RMR was measured by indirect calorimetry after an overnight fast and body composition was estimated by bioelectrical impedance analysis and predictive equations from the literature. Analysis of covariance was used to adjust RMR for body composition, body fat distribution and smoking habits. Additionally, RMR that is to be expected theoretically, was calculated on the basis of the subjects' body composition and the specific metabolic rate of the different organs and was compared to measured RMR. Results: Compared to young subjects adjusted RMR was significantly lower in elderly women (5432782 vs 5809770 kJ/day, Po0.01) and men (6971799 vs 75587121 kJ/day, Po0.001). In both elderly women and men, measured RMR was markedly lower than calculated RMR (À6257404, À5157570 kJ/day). By contrast, measured and calculated RMR were nearly the same in young men (1597612 kJ/day); in young women the difference between measured and calculated RMR was only À3007457 kJ/day. In both sexes, these differences are significantly larger in the elderly when compared to young adults. Conclusion: These results support the point of view that the decline in RMR with advancing age cannot be totally due to changes in body composition.

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“…For example, a recent review of the literature on risk preferences and smoking (Greiner 2004 ) shows that some papers find a correlation with proxies for risk aversion (Holt and Laury 2005 ), although the effect is often marginally significant, not robust to changes in the definition of 'smoker', and counterintuitive (i. e. smokers being more risk averse) (Johansson et al, 2009;Janssen, Katzmarzyk & Ross, 2004 ). An equal number of papers, however, fail to find significant association between risk preferences and smoking (Greiner, 2004;Guenther et al, 2006a;Hofstetter et al, 1986;Lahiri & Song, 2000;Lusk & Coble, 2005 ).…”

Section: Introductionmentioning

confidence: 99%

Are You What You Eat? Healthy Behaviour and Risk Preferences

Galizzi

Miraldo

2017

The B.E. Journal of Economic Analysis &Amp; Policy

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Abstract:We elicit and estimate risk preferences for a pool of young adults in the UK, and explore their links with healthy eating and risky health behaviours. We construct the Healthy Eating Index (HEI) as an overall indicator of nutritional quality, and we use it to complement the body mass index BMI. While for females we find no significant association between the BMI and risk preferences, males with high BMI appear more risk-seeking. However, this association disappears when controlling for the quality of the diet. For males, the HEI is significantly associated with risk preferences. Males smoking status is not associated with risk preferences.

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Increased 24-hour energy expenditure in cigarette smokers.

Cited by 65 publications

References 0 publications

Smoking status, cigarettes per day, and their relationship to overweight and obesity among former and current smokers in a national adult general population sample

Smoking status, cigarettes per day, and their relationship to overweight and obesity among former and current smokers in a national adult general population sample

Lower resting metabolic rate in the elderly may not be entirely due to changes in body composition

Are You What You Eat? Healthy Behaviour and Risk Preferences

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