Projects per year
Abstract
Objective: To determine whether body mass index (BMI), body fat percentage and waist circumference influence smoking behaviour.
Design: The association between genetic variants robustly associated with BMI, body fat percentage and waist circumference were evaluated in relation to three measures of smoking status and intensity in a Mendelian randomization framework.
Setting: The main analysis was based on UK Biobank with replication of results in the Tobacco and Genetics (TAG) consortium.
Participants: European descent participants from UK Biobank (n=375,434) and the TAG consortium (n=74,035).
Main outcome measures: Risk of current and past smoking; number of cigarettes smoked per day; age of smoking initiation.
Results: The Mendelian randomization (MR) analysis indicated that each standard deviation increment in BMI (4.6 kg/m2) increased the risk of being a smoker (odds ratio 1.18, 95% confidence interval 1.13 to 1.23, P= 3x10-14). This association was replicated in the TAG consortium data (1.19, 1.06 to 1.33, P= 4x10-3). Further, each standard deviation increment in BMI was estimated to increase smoking intensity by 0.88 cigarettes per day (0.50 to 1.26, P= 5x10-6) in UK Biobank and 1.27 cigarettes per day in the TAG consortium (0.46 to 2.07, P= 2.1x10-3). Similar results were also seen for body fat percentage and waist circumference in both UK Biobank and the TAG consortium data.
Conclusions: These results strongly suggest that higher adiposity influences smoking behavior and may have implications for the implementation of public health interventions aiming to reduce the prevalence of these important risk factors.
Design: The association between genetic variants robustly associated with BMI, body fat percentage and waist circumference were evaluated in relation to three measures of smoking status and intensity in a Mendelian randomization framework.
Setting: The main analysis was based on UK Biobank with replication of results in the Tobacco and Genetics (TAG) consortium.
Participants: European descent participants from UK Biobank (n=375,434) and the TAG consortium (n=74,035).
Main outcome measures: Risk of current and past smoking; number of cigarettes smoked per day; age of smoking initiation.
Results: The Mendelian randomization (MR) analysis indicated that each standard deviation increment in BMI (4.6 kg/m2) increased the risk of being a smoker (odds ratio 1.18, 95% confidence interval 1.13 to 1.23, P= 3x10-14). This association was replicated in the TAG consortium data (1.19, 1.06 to 1.33, P= 4x10-3). Further, each standard deviation increment in BMI was estimated to increase smoking intensity by 0.88 cigarettes per day (0.50 to 1.26, P= 5x10-6) in UK Biobank and 1.27 cigarettes per day in the TAG consortium (0.46 to 2.07, P= 2.1x10-3). Similar results were also seen for body fat percentage and waist circumference in both UK Biobank and the TAG consortium data.
Conclusions: These results strongly suggest that higher adiposity influences smoking behavior and may have implications for the implementation of public health interventions aiming to reduce the prevalence of these important risk factors.
| Original language | English |
|---|---|
| Article number | k1767 |
| Number of pages | 8 |
| Journal | BMJ |
| Volume | 361 |
| DOIs | |
| Publication status | Published - 16 May 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Research Groups and Themes
- ICEP
Fingerprint
Dive into the research topics of 'Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank'. Together they form a unique fingerprint.Projects
- 1 Finished
-
MRC UoB UNITE Unit - Programme 2
Relton, C. L. (Principal Investigator) & Relton, C. L. (Principal Investigator)
1/06/13 → 31/03/18
Project: Research
Profiles
-
Dr Philip C Haycock
- Epidemiology and Health Data Science - Senior Lecturer in Cancer Epidemiology
- Bristol Population Health Science Institute
- MRC Integrative Epidemiology Unit
Person: Academic , Member
-
Professor Richard M Martin
- Epidemiology and Health Data Science - Associate Pro Vice Chancellor (Research & Innovation) & Professor of Clinical Epidemiology
- Bristol Population Health Science Institute
- MRC Integrative Epidemiology Unit
- Cancer
Person: Academic , Member
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver