AF risk higher in those with long-term obesity and BMI variability
Weight and weight change and risk of atrial fibrillation: the HUNT study
Introduction and methods
The associations between obesity and AF risk are well established [1,2]. The incidence and prevalence of both conditions have risen substantially worldwide, with an accompanying rise in the burden on the medical system. Thus, a better understanding of risk factors for AF is needed.
Research on the link between obesity and AF often use measures for height and weight at a single timepoint, which do not account for the cumulative effect of obesity over the course of AF development, nor for the impact of long-term obesity or weight change. Some studies have used self-reported current and recalled earlier body weight, of which the latter is known to be inaccurate [3-5]. Studies that did use repeated body weight measurements, were limited by small sample size [3,6], short time intervals between measurements [4,6-8] or missing information on important covariates like comorbidity [3,4,6,7].
This large population-based study investigated the cumulative effects of obesity and weight change on AF risk over four decades. Repeated measurements of weight and height were used, as well as verified AF diagnoses and information on a wide range of CV risk factors was available. All 93,860 residents of at least 20 years old in a Norwegian County were invited to participate in HUNT-3 , from October 2006 to June 2008. 50,804 Inhabitants (54%) filled out questionnaires and underwent baseline clinical examinations. Height and weight information was also available from a mandatory tuberculosis screening conducted between 1966 and 1969, and from HUNT-1 and HUNT-2. 15,214 Individuals had information from all three previous measurements and were included in the main analysis.
- Current BMI was not strongly associated with the risk of AF, after adjustment for average BMI earlier in life. Average BMI earlier in life was associated with AF risk in overweight (HR: 1.2, 95%CI: 1.0-1.5) and obese individuals (HR: 1.6, 95%CI: 1.1-2.2) compared to those with normal weight, even after adjustment for BMI at the beginning of follow-up.
BMI change and risk of AF
- Those with loss or gain in BMI showed a higher AF risk, although not all hazards were significantly different from the references group with stable BMI (-2.5 to 2.5 change).
- The greatest risk increase was seen in those with ≥5 BMI points increase (HR: 2.6).
- Hazards were calculated for the early (1967-1985), middle (1985-1996) and late periods (1996-2007) and the highest (numerical) risks were seen in late periods. Correction for most recent BMI weakened the association of BMI loss, while that of BMI gain and AF was mostly unchanged.
Other body mass measures and risk of AF
- The highest vs. lowest degree of weight variability was associated with a higher risk of AF (HR: 1.5, 95%CI: 1.2-1.8). Average waist circumference (WC) >88/102 cm also associated with higher AF risk (HR: 1.2, 95%CI: 1.1-1.4) compared with those below this cut-off. The effects disappeared after adjustment for BMI.
- Average waist-hip ratio (WHR), change in WC or change in WHR were not associated with AF risk.
This large population-based study shows that long-term obesity and BMI change were associated with increased AF risk, also after accounting for current BMI. This underscores the relevance of considering weight history when assessing AF risk, rather than only considering current weight.
Middeldorp and colleagues  emphasize the global epidemic of obesity, and note that studies have mostly focused on older populations with obesity. There is growing recognition of primary prevention and the importance of long-term exposure to risk factors. This is relevant in the context of the fact that obesity is now also alarmingly prevalent in childhood.
A central strength of the study by Feng et al. is the availability of weight data over a 40 year period. With this data, the authors demonstrate that cumulative BMI over an extended period is a superior predictor of AF risk, compared to a single measurement, even though the latter may be more recent. This may not only be an effect of BMI earlier in life, as the authors postulate, but can also reflects the greater risk associated with longer exposure. These long-term observational data complement insights obtained in mendelian randomization studies.
The data on abdominal adiposity may seem confusing at first, as WC was associated with AF development but not WHR or change in either measurements. Middeldorp et al. find a possible explanation in a meta-analysis reporting risk estimates for different adiposity measurements and AF. The totality of observational data suggests that associations with AF appear strongest for WC and BMI. And more accurate quantification of adiposity may result in even stronger associations.
Among the limitations of the study are the fact that AF type (paroxysmal or persistent) was not available, and that the data points did not account for asymptomatic, or minimally symptomatic or subclinical groups of AF, which are increasingly recognized as important clinical entities. Moreover, it did not account of other time-varying risk factors that can contribute to AF.
In conclusion, the study by Feng et al. greatly advances our knowledge on the importance of long-term exposure to weight, weight gain and weight fluctuation for AF risk. Weight reduction and aggressive risk factor management strategies have been shown to improve AF outcomes in obese individuals. Efforts to address established obesity should be increased, and the complex mechanisms underpinning obesity and arrhythmogenesis should be unraveled, to refine our management approach to help these patients.
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