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Background: The main aim was to examine age-specific risk factor associations with incident atrial fibrillation (AF) and their attributable fraction in a large European cohort. Additionally, we aimed to examine risk of stroke and mortality in relation to new-onset AF across age., Methods: We used individual-level data (n=66 951, 49.1% men, age range 40-98 years at baseline) from five European cohorts of the MOnica Risk, Genetics, Archiving and Monograph Consortium. The participants were followed for incident AF for up to 10 years and the association with modifiable risk factors from the baseline examinations (body mass index (BMI), hypertension, diabetes, daily smoking, alcohol consumption and history of stroke and myocardial infarction (MI)) was examined. Additionally, the participants were followed up for incident stroke and all-cause mortality after new-onset AF., Results: AF incidence increased from 0.9 per 1000 person-years at baseline age 40-49 years, to 17.7 at baseline age ≥70 years. Multivariable-adjusted Cox models showed that higher BMI, hypertension, high alcohol consumption and a history of stroke or MI were associated with increased risk of AF across age groups (p<0.05). Between 30% and 40% of the AF risk could be attributed to BMI, hypertension and a history of stroke or MI. New-onset AF was associated with a twofold increase in risk of stroke and death at ages≥70 years (p≤0.001)., Conclusion: In this large European cohort aged 40 years and above, risk of AF was largely attributed to BMI, high alcohol consumption and a history MI or stroke from middle age. Thus, preventive measures for AF should target risk factors such as obesity and hypertension from early age and continue throughout life., Competing Interests: Competing interests: RBS has received lecture fees and advisory board fees from BMS/Pfizer outside this work., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Physical activity and overweight are associated with myocardial infarction (MI). However, their joint association with MI remains unclear. Our objective was to examine the independent and joint association between leisure-time physical activity (LTPA), body mass index (BMI) and MI. This prospective cohort study included 16,572 men and women (47.5% women) aged 20-54 years who took part in the second Tromsø Study. At baseline in 1979-80 LTPA was assessed by questionnaire. Data on MI was collected and adjudicated through hospital and causes of death registries between 1979 and 2013. Cox proportional hazards models were used to examine the independent and joint associations between LTPA, BMI and MI. The final sample included 16,104 individuals. During a median follow up of 34 years, 1613 incident cases of MI were recorded. Physical inactivity and elevated BMI were both independently associated with MI (p for trend 0.02 and <0.001). In joint analyses, normal weight, inactive individuals had a 20% higher risk of MI compared to their active counterparts (hazard ratio (HR) 1.20 (1.02-1.41)). The highest risk of MI was seen in obese, inactive individuals when compared to normal weight, active individuals (HR 3.20 (2.30-4.44)). The risk of MI increased with increasing BMI regardless of the activity level. HRs were lower for active compared to inactive individuals within the same BMI category. The findings suggest that LTPA and BMI are independently associated with risk of MI. LTPA seems to attenuate but not eliminate the risk of MI associated with excess bodyweight., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Atrial fibrillation (AF) prevalence is increasing, and body mass index (BMI) is a risk factor for AF. However, sex differences in the impact of BMI on AF risk have not been fully elucidated., Methods and Results: Data from the fourth survey (1994-1995) of the Tromsø Study (Norway) were used to investigate the association of single-measurement BMI on future AF risk. To analyze the influence of BMI changes on AF risk, data from individuals who attended the third and fourth study surveys were used. AF diagnosis was derived from record linkage and end point adjudication. Cox regression analysis was conducted using fractional polynomials of BMI and BMI change with models adjusted for age, baseline BMI (change analyses), risk factors, comorbidities, and antihypertensive medications.Data were available for 24 799 individuals from the fourth survey (mean age, 45.5±14.2 years; 52.9% women). Over 15.7±5.5 years, 811 women (6.2%) and 918 men (7.9%) developed AF. In men, lower BMI decreased AF risk and higher BMI increased risk (hazard ratios [95% confidence intervals] for BMI 18 or 40 kg/m 2 compared with 23 kg/m 2 were 0.75 [0.70-0.81] and 4.42 [3.00-6.53], respectively). The same pattern was identified in women. Two surveys were attended by 14 652 individuals. In men and women, a decrease in BMI over time was associated with decreased AF risk and an increase in BMI was associated with increased AF risk., Conclusions: Within a population cohort, BMI was positively associated with AF risk. Change in BMI over time influenced AF risk in both men and women., (© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)

Background: Body mass index (BMI) and smoking have been positively associated with hemoglobin concentration, and both are risk factors for cardiovascular disease., Objective: The aim of this study was to assess whether there were sex differences in how changes in BMI and smoking habits influenced hemoglobin concentration., Methods: In 1994-95 and 2001-02, a longitudinal, population-based study was conducted in the municipality of Tromsø, in northern Norway. Inhabitants aged > or =25 years were invited to participate. Participants replied to a questionnaire regarding health, physical activity, coffee and alcohol consumption, and smoking habits. Blood samples were drawn to analyze hemoglobin concentration. All analyses were performed separately for each sex. Differences between 1994-95 and 2001-02 were examined with t or chi(2) (McNemar) tests for paired data. Cross-sectional comparisons were made using 2-sample t tests. Different models of univariate and multiple linear regression analyses were used to investigate the impact of the various variables on hemoglobin change., Results: Data from a total of 2105 men and 2945 women were examined. At baseline, mean age was 58.9 years for men (range, 25-78 years) and 57.8 years for women (range, 25-82 years); mean BMI was 26.1 kg/m(2) for men and 25.8 kg/m(2) for women. In men, hemoglobin decreased with age, on average from 147.5 to 145.1 g/L. In women, hemoglobin decreased from 135.6 to 134.7 g/L, but increased with increasing age up to 54 years, and thereafter decreased gradually. Mean BMI increased 0.8 kg/m(2) in men and 1.2 kg/m(2) in women. In total, 394 of 2057 men (19%) and 499 of 2889 women (17%) stopped smoking or smoked fewer cigarettes per day. In a univariate regression model, an increase of 1 kg/m(2) in BMI was associated with an increase in hemoglobin of 1.1 g/L (95% CI, 0.84 to 1.27) in men and 0.4 g/L (95% CI, 0.30 to 0.56) in women. In another univariate model, smoking cessation was associated with a decrease in hemoglobin of 1.9 g/L (95% CI, -3.32 to -0.56) in men and 1.7 g/L (95% CI, -2.93 to -0.56) in women. In men who smoked less and had a BMI increase of >2.5 kg/m(2), hemoglobin decreased 0.3 g/L. In contrast, hemoglobin decreased 3.4 g/L in men who smoked less and lost weight (P for trend, < 0.001 by changing BMI). Women who smoked less had a decrease in hemoglobin independent of BMI changes., Conclusions: The positive association between an increase in BMI and hemoglobin was stronger in men than in women. The effect of smoking reduction on hemoglobin was attenuated with increasing BMI in men, but not in women., (Copyright (c) 2010 Excerpta Medica Inc. All rights reserved.)

Haemoglobin level declines with increasing age in cross sectional studies. Little is known about the longitudinal changes of haemoglobin. Because both high or low haemoglobin levels increase mortality and morbidity we examined how changes in lifestyle factors like body mass index (BMI) and smoking habits influence cohort changes in haemoglobin level. In all, 4159 men aged 20-49 years at baseline were examined in 1974 and 1994-1995 in a longitudinal, population-based study from the municipality of Tromsø, Northern Norway. Mean haemoglobin was 148 g/l. There was no difference in mean haemoglobin after 20 years in any strata of age. Mean BMI increased 2.1 kg/m(2). The prevalence of smokers decreased 20.1 percentage points. In a multiple regression analysis increase in BMI was associated with increased haemoglobin change. Smoking cessation lowered mean haemoglobin 1.6 g/l compared to never smokers. Haemoglobin increased 0.8 g/l in smoking quitters whose BMI increased >2.5 kg/m(2) compared to a decrease of 6.7 g/l in weight reducers. There was a positive dose-response relationship between changes in cigarettes smoked per day and change in haemoglobin among consistent smokers. In conclusion, in contrast to cross sectional studies, mean haemoglobin did not change during 20 years ageing of relatively young men. This could be explained by higher BMI and less smoking. The increase in BMI affected haemoglobin change to such an extent that the reduction in haemoglobin due to smoking cessation was counteracted. Prospective studies are needed to address the health implications.

Background: Atrial fibrillation represents a substantial clinical and public health issue. The definitive impact of body mass index on prognosis of patients with chronic (persistent or permanent) atrial fibrillation remains undetermined. Aim: The purpose of this study was to investigate the association of body mass index with health outcomes (mortality and re-hospitalisation) of patients with chronic atrial fibrillation. Methods: Using data from the Standard versus Atrial Fibrillation spEcific managemenT strategY (SAFETY) trial (a randomised controlled trial of home-based, atrial fibrillation-specific disease management), we performed post-hoc analyses of mortality and re-hospitalisation outcomes during minimum 24-month follow-up according to baseline body mass index profile. Results: Of 297 participants (mean age 71±11 years, 47% female, mean body mass index 29.6±6.7 kg/m2), 35.0% of participants were overweight (body mass index 25.0–29.9 kg/m2) and 43.1% were obese (body mass index≥30 kg/m2). During follow-up, n=42 died including 16/65 (24.6%) classified as normal body mass index, 16/104 (15.4%) classified as overweight and 10/128 (7.8%) classified as obese. Increasing body mass index was not associated with increased mortality but was associated with re-hospitalisation due to cardiovascular disease with greater length-of-stay (odds ratio 1.05; 95% confidence interval 1.00–1.09, p=0.032). Obese individuals experienced increased unplanned admissions compared to overweight individuals (incidence rate ratio 0.71; 95% confidence interval 0.53–0.96, p=0.028), and increased cardiovascular-related (incidence rate ratio 0.58; 95% confidence interval 0.39–0.86, p=0.007) and all-cause admissions (incidence rate ratio 0.63; 95% confidence interval 0.45–0.89, p=0.008) compared to those classified as normal body mass index. Conclusion: Overweight and obesity were not associated with survival in patients with chronic atrial fibrillation but were associated with more frequent hospital care and prolonged stay. [ABSTRACT FROM AUTHOR]

Background: Single measurements of modifiable risk factors may underestimate associations with outcomes in cohorts. We aimed to compare risk estimates of myocardial infarction (MI) and venous thromboembolism (VTE) by atherosclerotic risk factors during long follow-up using time-fixed analyses without and with correction for regression dilution and time-varying analyses. Methods: The study included 5970 subjects enrolled in the fourth survey of the Tromsø Study (1994/95). Blood pressure, lipid levels, body mass index (BMI), diabetes and smoking status were measured at baseline, and subjects still alive at the fifth (2001/02, n = 5179) and sixth (2007/08, n = 4391) survey were re-measured. Incident events of MI (n = 714) and VTE (n = 214) were recorded until December 2010. Time-fixed and time-varying Cox regression models were used to estimate hazard ratios (HR) for MI and VTE adjusted for age and sex. Results: Variations in BMI, blood pressure and lipid levels were small, and did not alter the risk estimates when time-varying analyses were compared to time-fixed analyses. For MI, variables that changed considerably over time yielded the greatest changes in risk estimates (HR for smoking changed from 1.80 (95% CI 1.55–2.10) to 2.08 (95% CI 1.78–2.42)). For VTE, only BMI was associated with increased risk in both time-fixed and time-varying analysis, but the risk estimates weakened in the time-varying analysis. Correction of time-fixed HRs with Rosner´s method tended to overestimate risk estimates compared to time-varying analysis. Comment: For MI and VTE, risk estimates based on baseline and repeated measures corresponded well, whereas correction for regression dilution tended to overestimate risks. [ABSTRACT FROM AUTHOR]

Objective To investigate the association between echocardiographic measurements with emphasis on diastolic dysfunction and risk of atrial fibrillation (AF) in a population-based cohort study. Methods We followed 2406 participants from the Tromsø Study from 1994 to 2010. Left atrial (LA) size and mitral Doppler indices as measured by echocardiography were used for evaluating diastolic dysfunction. Information concerning age, systolic blood pressure, height, heart rate, body mass index, total and high-density lipoprotein cholesterol, self-reported use of alcohol, smoking, coffee, physical activity, antihypertensive treatment, prevalent coronary heart disease, valvular heart disease, heart failure, hypertrophy, diabetes and palpitations were obtained at baseline. The outcome measure was clinical AF, documented by an ECG. Results AF was detected in 462 subjects (193 women). Mean age at baseline was 62.6 years. Incidence rate of clinical AF was 12.6 per 1000 personyears. In multivariable Cox proportional hazards regression analysis, moderately enlarged LA was associated with 60% (95% CI 1.2 to 2.0) increased risk of AF. Severely enlarged LA had HR for AF of 4.2 (95% CI 2.7 to 6.5) with p value for linear trend <0.001, and the association was similar in both sexes. Abnormal mitral Doppler flow adjusted for predictor variables did not show a statistically significant association with AF risk. However, when LA size was also adjusted for, the risk of AF increased by 30% (95% CI 1.0 to 1.6). Conclusions Our findings suggest that enlarged LA as a measure for diastolic dysfunction is a significant risk factor for AF in both sexes, and adding measures of abnormal diastolic flow increased the predictive ability significantly. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Tracking of cardiovascular risk factors (blood pressure, body mass index (BMI), and serum lipids) has not been studied much in a general, adult population. No known study has compared tracking of these factors for both sexes. In the present study, 17,710 men and women aged 20-61 years at baseline attended two or three population-based health surveys in Tromsø, Norway, over 16 years (between 1979-1980 and 1994-1995). Tracking coefficients were estimated by using different methods, and possible predictors of tracking were found. There was a high degree of tracking for BMI (overall tracking coefficients: 0.85 for men, 0.80 for women). Relatively high (or moderate) tracking was found for systolic blood pressure (respective sex-specific coefficients: 0.52, 0.54), diastolic blood pressure (0.48, 0.48), high density lipoprotein cholesterol (0.55, 0.64), and total cholesterol (0.77, 0.65). The lowest coefficients were for triglycerides (0.43, 0.39). Analysis of tracking in the upper sextile confirmed these results. Although some baseline predictors were associated with tracking, the effects were relatively weak. When predictors for tracking in the upper sextile were assessed, significant associations were found with relatively strong effects. No major sex differences were observed in tracking. However, women were more likely than men to remain in the upper sextile of systolic and diastolic blood pressures and of BMI. [ABSTRACT FROM AUTHOR]

The increase of obesity coincides with a substantial decrease in cigarette smoking. We assessed post-cessation weight change and its contribution to the obesity epidemic in a general population in Norway. A total of 14,453 participants (52.6% women), aged 25-54 years in 1994, who attended at least two of four surveys in the Tromsø Study between 1994 and 2016, were included in the analysis. Hereof 77% participated in both the first and the last survey. Temporal trends in mean body mass index (BMI), prevalence of obesity (BMI ≥ 30 kg/m2) and daily smoking were estimated with generalized estimation equations. We assessed BMI change by smoking status (ex-smoker, quitter, never smoker, daily smoker), and also under a scenario where none quit smoking. In total, the prevalence of daily smoking was reduced over the 21 years between Tromsø 4 (1994-1995) and Tromsø 7 (2015-2016) by 22 percentage points. Prevalence of obesity increased from 5 - 12% in 1994-1995 to 21-26% in 2015-2016, where obesity in the youngest (age 25-44 in 1994) increased more than in the oldest (p < 0.0001). Those who quit smoking had a larger BMI gain compared to the other three smoking subgroups over the 21 years (p < 0.0001). The scenario where none quit smoking would imply a 13% reduction in BMI gain in the population, though substantial age-related differences were noted. We conclude that smoking cessation contributed to the increase in obesity in the population, but was probably not the most important factor. Public health interventions should continue to target smoking cessation, and also target obesity prevention. [ABSTRACT FROM AUTHOR]