| Title |
Active and passive smoking and the risk of myocardial infarction in 24,968 men and women during 11 year of follow-up: the Tromsø Study
|
|---|---|
| Published in |
European Journal of Epidemiology, February 2013
|
| DOI | 10.1007/s10654-013-9785-z |
| Pubmed ID | |
| Authors |
Birgitte Iversen, Bjarne K. Jacobsen, Maja-Lisa Løchen |
| Abstract |
Active smoking is a well-established risk factor for myocardial infarction, but less is known about the impact of passive smoking, and possible sex differences in risk related to passive smoking. We investigated active and passive smoking as risk factors for myocardial infarction in an 11-year follow-up of 11,762 men and 13,206 women included in the Tromsø Study. There were a total of 769 and 453 incident cases of myocardial infarction in men and women, respectively. We found linear age-adjusted relationships between both active and passive smoking and myocardial infarction incidence in both sexes. The relationships seem to be stronger for women than for men. Age-adjusted analyses indicated a stronger relationship with passive smoking in ever-smokers than in never-smokers. After adjustment for important confounders (body mass index, blood pressure, total cholesterol, HDL cholesterol and physical activity) the associations with active and passive smoking were still statistically significant. Adjusting for active smoking when assessing the effect of passive smoking and vice versa, indicated that the effect of passive smoking in men may be explained by their own active smoking. In women, living with a smoker ≥30 years after the age of 20 increased the myocardial infarction risk by 40 %, even after adjusting for active smoking. Passive smoking is a risk factor for myocardial infarction on its own, but whereas the effect for men seems to be explained by their own active smoking, the effect in females remains statistically significant. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 1 | 25% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 2 | 2% |
| Brazil | 1 | 1% |
| Unknown | 84 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 13 | 15% |
| Researcher | 11 | 13% |
| Student > Ph. D. Student | 7 | 8% |
| Student > Master | 7 | 8% |
| Student > Postgraduate | 6 | 7% |
| Other | 18 | 21% |
| Unknown | 25 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 35 | 40% |
| Nursing and Health Professions | 7 | 8% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Computer Science | 4 | 5% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 4 | 5% |
| Unknown | 30 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2013.
All research outputs
#14,580,305
of 25,059,640 outputs
Outputs from European Journal of Epidemiology
#1,330
of 1,785 outputs
Outputs of similar age
#107,446
of 198,202 outputs
Outputs of similar age from European Journal of Epidemiology
#20
of 32 outputs
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