Weight Concerns Among Finnish Ever-Smokers: A Population-Based Study

Luostarinen, Mikko; Tuovinen, Eeva-Liisa; Saarni, Suoma; Kinnunen, Taru; Hukkinen, Maria; Haukkala, Ari; Patja, Kristiina; Kaprio, Jaakko; Korhonen, Tellervo

doi:10.1093/ntr/ntt043

Cited by 19 publications

(20 citation statements)

References 35 publications

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“…In a study of almost 2000 smokers in the USA, recruited into a trial of bupropion and/or nicotine inhalers to promote cessation, 50% of female and 26% of male smokers reported that gaining weight discouraged them from trying to quit, 2 while among adults in Finland, daily smokers were found to report more weight concerns than former smokers or occasional smokers. 3 …”

Section: Introductionmentioning

confidence: 99%

Heavier smoking may lead to a relative increase in waist circumference: evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium

et al. 2015

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ObjectivesTo investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity.DesignMendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes.Participants148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA).Primary outcome measuresWaist and hip circumferences, and waist-hip ratio.ResultsThe data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by −0.40% (95% CI −0.57% to −0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being −0.31% (95% CI −0.42% to −0.19), −0.08% (−0.19% to 0.03%) and −0.74% (−0.96% to −0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (−0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (−0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele.ConclusionsFor a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity.

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Section: Introductionmentioning

confidence: 99%

Heavier smoking may lead to a relative increase in waist circumference: evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium

et al. 2015

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“…This process likely explains why smokers tend to decrease body weight, and why smoking cessation is frequently followed by weight gain. As a result, one of the barriers to quitting is the fear of gaining weight [31]. …”

Section: Discussionmentioning

confidence: 99%

General and Abdominal Obesity Is Related to Physical Activity, Smoking and Sleeping Behaviours and Mediated by the Educational Level: Findings from the ANIBES Study in Spain

López-Sobaler¹,

Rodríguez-Rodríguez²,

Aranceta-Bartrina³

et al. 2016

PLoS ONE

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The aim of the present study was to analyze the association of socioeconomic (SES) and lifestyle factors, with the conditions of overweight (OW), general (OB) and abdominal obesity (AO) in Spanish adults. A representative sample of 1655 Spanish adults (18 to 65 years) from the ANIBES Study was investigated. Collected data included measured anthropometry (weight, height and waist circumference), demographic and SES data (region and habitant population size, educational level, family income, unemployment rate), physical activity (PA) and other lifestyle factors (sleeping time and frequency of viewing television). OW, OB and AO were determined in each participant. Being male, older than 40 years, and watching television more frequently were associated with higher risk of OB and AO, whereas those with a higher level of education, smokers, and more time in sleeping and in vigorous PA, but not in moderate-vigorous PA, were associated with a lower risk. Living in the Atlantic region and stating no answer to the question regarding family income were also associated with lower risk of AO. Strategies for preventing and reducing OB and AO should consider improving sleeping habits and PA. They should also pay more attention to the most vulnerable groups such as those less educated.

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“…The majority of women who quit smoking gain 8 to 10 lb on average [9][10][11][12][13]. Many women smokers report concerns about weight gain as a barrier to quitting [14][15][16][17][18][19][20][21][22][23][24][25], and women quitters who return to smoking identify weight gain as a reason for their relapse [26][27][28][29]. Women who are highly concerned about their weight are more likely to smoke as a means to control their weight [15,30,31].…”

Section: Introductionmentioning

confidence: 99%

Development and evaluation of the See Me Smoke-Free multi-behavioral mHealth app for women smokers

Gordon

Armin

Hingle

et al. 2017

Behav. Med. Pract. Policy Res.

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Women face particular challenges when quitting smoking, especially those with weight concerns. A multi-behavioral smoking cessation intervention addressing these concerns and incorporating guided imagery may assist women to engage in healthy lifestyle behaviors. An mHealth app can easily disseminate such an intervention. The goals of this pilot study were to develop and test the feasibility and potential of the See Me Smoke-Free ™ mHealth app to address smoking, diet, and physical activity among women smokers. We used pragmatic, directto-consumer methods to develop and test program content, functionality, and the user interface and conduct a pre-/post-test, 90-day pilot study. We enrolled 151 participants. Attrition was 52%, leaving 73 participants. At 90 days, 47% of participants reported 7-day abstinence and significant increases in physical activity and fruit consumption. Recruitment methods worked well, but similar to other mHealth studies, we experienced high attrition. This study suggests that a guided imagery mHealth app has the potential to address multiple behaviors. Future research should consider different methods to improve retention and assess efficacy.

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Weight Concerns Among Finnish Ever-Smokers: A Population-Based Study

Cited by 19 publications

References 35 publications

Heavier smoking may lead to a relative increase in waist circumference: evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium

Heavier smoking may lead to a relative increase in waist circumference: evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium

General and Abdominal Obesity Is Related to Physical Activity, Smoking and Sleeping Behaviours and Mediated by the Educational Level: Findings from the ANIBES Study in Spain

Development and evaluation of the See Me Smoke-Free multi-behavioral mHealth app for women smokers

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