Non-traditional risk factors for atrial fibrillation: epidemiology, mechanisms, and strategies

Abstract

Atrial fibrillation (AF) has become the pre-dominant arrhythmia worldwide and is associated with high morbidity and mortality. Its pathogenesis is intricately linked to the deleterious impact of cardiovascular risk factors, emphasizing the pivotal imperative for early detection and mitigation strategies targeting these factors for the prevention of primary AF. While traditional risk factors are well recognized, an increasing number of novel risk factors have been identified in recent decades. This review explores the emerging non-traditional risk factors for the primary prevention of AF, including unhealthy lifestyle factors in current society (sleep, night shift work, and diet), biomarkers (gut microbiota, hyperuricaemia, and homocysteine), adverse conditions or diseases (depression, epilepsy, clonal haematopoiesis of indeterminate potential, infections, and asthma), and environmental factors (acoustic pollution and other environmental factors). Unlike traditional risk factors, individuals have limited control over many of these non-traditional risk factors, posing challenges to conventional prevention strategies. The purpose of this review is to outline the current evidence on the associations of non-traditional risk factors with new-onset AF and the potential mechanisms related to these risk factors. Furthermore, this review aims to explore potential interventions targeting these risk factors at both the individual and societal levels to mitigate the growing burden of AF, suggesting guideline updates for primary AF prevention.

Graphical Abstract

Emerging non-traditional risk factors for new-onset atrial fibrillation include lifestyle factors, biomarkers, adverse conditions or diseases, and environmental factors. CHIP, clonal haematopoiesis of indeterminate potential; RAAS, renin-angiotensin-aldosterone system.

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Introduction

Atrial fibrillation (AF) is the most common type of sustained arrhythmia, accounting for significant morbidity and mortality.¹ According to the 2021 Global Burden of Disease (GBD) study, AF/atrial flutter affected 52.55 million individuals worldwide, a 137% increase from 1990, and associated deaths have doubled since 1990.² In contrast to the previous definition based on the arrhythmia duration, the new categorization proposed by the most recent guideline describes AF as a progressive disease that includes different stages (at risk for AF, pre-AF, AF, and permanent AF).¹ This emphasizes the importance of prevention and risk factor management at the earliest stage.

Accounting for nearly 8%–40% of disability-adjusted life years (DALYs) of AF from data in the GBD, the traditional risk factors for AF include demographic, anthropometric, and cardiovascular risk factors such as lack of physical activity, smoking, and obesity; cardiovascular disease (CVD); non-cardiac conditions; and genetic markers (at least 138 AF loci identified in single variant testing and causative mutations found in large families or populations such as the ion channel KCNQ1, the cardiac peptide NPPA, the transcription factor TBX5, and a motor protein MYL4).^1,3–8 Therefore, the HEAD-2-TOES (heart failure, exercise, arterial hypertension, Type 2 diabetes mellitus, tobacco smoking, obesity, ethanol consumption, and sleep apnoea) scheme was proposed to target the management of traditional risk factors for AF.³ Interestingly, among 15 400 individuals with AF in 47 countries, almost all patients without traditionally defined AF-risk factors have a favourable 1 year prognosis, but the risk of AF-related rehospitalization remains high.⁹ This observation calls for the identification of yet-undiscovered aetiologies and beyond traditional risk factors for AF. After recent years of research into natural, built, and social environments, more potential risk factors, including unhealthy lifestyle factors, novel biomarkers, adverse conditions or diseases, and natural environmental factors, have been discovered. These factors extend beyond traditional risk factors and are emerging as non-traditional risk factors for AF (Table 1). For example, the percentage of DALYs attributable to dietary risks for AF was 6.45% in the GBD. The population attributable risk from broad depression, severe air pollution, and acute illness were 0.8%–3.0%, 0.9%–2.2%, and 11.2%–16.2%, respectively, across different ages.⁵ Traditional and non-traditional risk factors may interact to induce the components of biological responses and drivers (such as microbiota changes, oxidative stress, inflammation, and autonomic dysfunction) to increase the risk of AF. However, individuals have little control over some of these factors, and they cannot be directly modified similar to traditional risk factors, which may lead to the failure of traditional prevention strategies.¹⁰ Thus, studies on the epidemiology, mechanism, and strategy of non-traditional risk factors for AF are highly warranted.

In this state-of-the-art review, we discuss emerging non-traditional risk factors for the primary prevention of AF and consider the pathophysiological mechanisms involved. We also explore how these risk factors could be targeted at the individual, healthcare, and social levels, ultimately reducing the global burden of this common and debilitating condition (Graphical Abstract).

Search strategy and selection criteria

We conducted a non-systematic literature review focusing on recent studies related to AF. First, we excluded risk factors recognized in the 2023 ACC/AHA/ACCP/HRS Guideline¹ and 2024 ESC Guideline.¹¹ Second, we searched references in multiple electronic databases (including PubMed, MEDLINE, and Web of Science) up to September 2024 to identify original research, meta-analyses, and review articles published in peer-reviewed journals that examined the associations beyond traditional risk factors with AF.¹ Third, we structured the results on the basis of the classification of non-traditional risk factors for CVD in a previous review^10,12 and prioritized studies with prospective designs and large sample sizes, preferably in diverse populations. Finally, lifestyle factors (sleep, night shift work, and diet), biomarkers [gut microbiota, hyperuricaemia, and homocysteine (Hcy)], adverse conditions or diseases [depression, epilepsy, clonal haematopoiesis of indeterminate potential (CHIP), infections, and asthma], and environmental factors (acoustic pollution and other environmental factors, including climate change and greenness) were incorporated into the search strategy.

Non-traditional risk factors

Lifestyle

Sleep

In Life’s Essential 8, sleep health has been included as a new component.¹³ Globally, more than one-third of adults sleep less than the recommended 7 h per night advised by the American Academy of Sleep Medicine and Sleep Research Society,¹⁴ suggesting an ongoing need for public awareness about sleep. In a prospective cohort study with more than 0.4 million participants, only 21% of individuals had a healthy sleep score of 5, including chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. They had a 29% lower risk of incident AF than those with a poor sleep pattern did.¹⁵ When assessed separately, two meta-analyses reported a 6% and 21% increased risk of AF for individuals with short sleep durations.^16,17 This significant association was inconsistent among various observational studies and Mendelian randomization (MR) studies, likely due to differences in the study population.^16,18–20 Compared with non-nappers, those who usually napped were significantly associated with a 14%–28% greater risk of incident AF.²¹

The mechanisms included sympathetic nervous system activation^22,23 and a broad range of metabolic changes, such as increased blood pressure,²⁴ chronic inflammation,^25,26 and oxidative stress^27,28 (Figure 1). Specifically, insomnia can activate the hypothalamic-pituitary-adrenocortical axis, especially when associated with short objective sleep duration.²⁹ This persistent state of sympathetic activation and increased cardiovascular burden may have adverse effects on cardiac structure and function, thereby increasing the risk of AF.³⁰

Currently, there is a growing view that a healthy sleep pattern probably reduces the risk of CVD and AF.^15,31,32 Awareness of avoiding sleep restriction should be implemented. According to authoritative statements, ≥7 h of sleep per night is recommended for adults ‘to promote optimal health’.^14,33

Night shift work

Data from the sixth European Working Conditions Survey showed that nearly 21% of the working population is engaged in shift work to meet the demands of a 24-h economy.³⁴ However, long-term shift work, especially night shift work, may disrupt the circadian rhythms of the body and lead to abnormal sleep patterns.³⁵ A recent study revealed that a duration of more than 10 years and an average of three to eight night shifts per month were significantly associated with 22% and 37% greater risks of incident AF, respectively.³⁶ Moreover, shift work was associated with a 10 year incidence of AF in individuals <40 years.³⁷ However, another cohort study with healthcare workers did not find a significant excess risk of AF related to night shift work or long working hours.³⁸ This may be due to the younger age of the population, with a mean age of under 50 years. When an accelerometer was used to objectively quantify the rest–activity rhythm,³² late peak activity was associated with an increased risk of AF among the general population, indicating that circadian disruption could predict the onset of AF in the general population.

Night shift work can lead to long working hours, chronic fatigue, sleep disruption, and increased stress, which may negatively impact cardiovascular health and increase the risk of AF^39,40,41 (Figure 1). Furthermore, shift work may affect the stability and rhythm of the cardiovascular system, influencing cardiac electrical activity. The underlying mechanisms, including activation of the sympathetic nervous system,⁴² excessive secretion of norepinephrine,⁴³ inflammation,⁴⁴ oxidative stress,⁴⁵ and changes in lifestyle behaviours such as diet and physical activity,⁴⁶ have been increasingly implicated in the association between night shift work and AF.

To promote a healthy labour market, the Institute for Public Policy Research proposed that the government should introduce new labour market regulations, including the right to a 2 week notice period of their shifts and the right to compensation if this is not followed for people working irregular hours or shifts.⁴⁷ To implement these strategies, discussions with all stakeholders will need to be held, and government responses will be implemented.

Diet

Global Burden of Disease has provided a comprehensive picture of the health effects of poor dietary habits.⁴⁸ Especially, it suggested that non-optimal intake of whole grains, fruits, and sodium accounted for over 50% of deaths and 66% of DALYs attributable to diet.⁴⁸ A prospective cohort study demonstrated a negative correlation between the Mediterranean Diet Adherence Screener score and the presence of AF,⁴⁹ similar to case-control results.⁵⁰ Another diet type, the EAT-Lancet diet, was proposed by the EAT-Lancet Commission in 2019.⁵¹ A prospective cohort study in Sweden revealed that the highest group for the EAT-Lancet diet index was associated with a 16% lower risk of AF than the lowest index group.⁵² More specifically, ultra-processed food,⁴⁹ sugar-sweetened or artificially sweetened beverages,⁵³ a high-phosphate diet,⁵⁴ and a low-carbohydrate diet⁵⁵ were estimated to be related to an increased risk of AF. However, extra virgin olive oil⁵⁶ and moderate consumption of coffee may reduce the incidence of AF.^57,58,59 However, MR studies did not support the causal association between coffee consumption and the risk of AF,^60,61 which should be cautiously interpreted due to bias and confounders.

The association between diet and AF risk may occur through indirect pathways that affect the susceptibility to adverse conditions or diseases associated with AF⁶² (Figure 1). Adherence to a plant-based diet reduces the likelihood of AF-risk factors such as hypertension,⁶³ obesity,⁶⁴ diabetes,⁶⁵ and coronary heart disease.⁶⁶ Nevertheless, the direct effects of diet on the composition of the gut microbiota and inflammation should not be overlooked.^67,68 In addition, evidence has demonstrated that greater adherence to a Mediterranean diet is associated with a significant reduction in the amount of epicardial adipose tissue in people with AF, and excess epicardial adipose tissue is strongly associated with persistent AF.⁶⁹

Although data on preventive measures are not univocal, there is increasing awareness of the impact of diet on AF. The Mediterranean diet plus oil, the Dietary Approaches to Stop Hypertension diet, and the EAT-Lancet diet are recommended for heart health.⁵⁶ More detailed information on a healthy diet is presented in Table 2.

Biomarkers

Gut microbiota

The gut microbiota is increasingly recognized for its potential role in cardiovascular health.⁷⁰ Recent studies have delved into the disparities in the gut microbiome between individuals afflicted with or without AF,⁷¹ those with various AF subtypes,⁷² and those with AF of varying chronicity,⁷³ indicating a correlation between specific perturbations in the gut microbiota composition and the onset/persistence of AF episodes. Genetic evidence from 430 000 participants indicates a causal relationship of two specific microbial taxa with incident AF: the species Eubacterium ramulus and the genus Holdemania.⁷⁴ Furthermore, trimethylamine N-oxide (TMAO), a metabolite from the gut microbiota, was found to be predictive of AF.⁷⁵

The mechanisms are not yet fully understood. Metabolites produced by the gut microbiota may influence immune responses and inflammation, processes that contribute to the structural and electrical remodelling of the atria⁷⁶ (Figure 2). The gut–immune–heart axis shows that the gut microbiota can indirectly induce AF by modulating the immune system.⁷⁶ This includes the recruitment and phenotypic changes of monocytes and macrophages, as well as the specific roles of cytokines released by leucocytes. Additionally, the gut microbiota may interact with the autonomic nervous system, potentially influencing the cardiac rhythm through the production of short-chain fatty acids and other neurotransmitters.⁷⁷ The complex interplay between the gut microbiota and various host factors, such as genetics, diet, and antibiotic use, further complicates this relationship.

To enhance cardiovascular health, it is advisable to take measures to modulate the microbiome, including dietary interventions, probiotic/prebiotic supplementation, and symbiotic and faecal microbiota transplantation.⁶⁷ However, further research on whether the strategies to prevent and treat gut dysbiosis could contribute to AF development is needed.

Hyperuricaemia

Hyperuricaemia is estimated to affect ∼14.0%, 20.0%, and 24.5% of adults in China,⁷⁸ the USA,⁷⁹ and Ireland,⁸⁰ respectively. A meta-analysis of eight cohort studies reported its close relationship with AF.⁸¹ A similar result was found in another large prospective cohort of 339 604 individuals with a follow-up of 25.9 years.⁸² Compared with the lowest uric acid quartile, the adjusted hazard ratio (HR)s for the second, third, and fourth quartiles were 1.09, 1.19, and 1.45, respectively. Hyperuricaemia may not only operate through CVD to increase the risk of AF but also has a direct influence on the development of AF via mechanisms including oxidative stress, inflammation, insulin resistance, and activation of the renin-angiotensin-aldosterone system, all of which could ultimately induce electrical remodelling, autonomic nervous system changes, Ca²⁺ handling abnormalities, and atrial remodelling^82,83 (Figure 2). For example, high serum uric acid can increase reactive oxygen species via ERK/p38 activation and PI3K/Akt inhibition, and increased reactive oxygen species interfere with the IRS1/Akt pathway to induce insulin resistance in cardiomyocytes.⁸⁴ Moreover, the urate-lowering medication febuxostat was also found to be associated with a greater risk of AF than allopurinol was, especially among patients with an 80 mg/day dose and in the first 6 months of use.⁸⁵ Therefore, in addition to preventing hyperuricaemia through lifestyle interventions, it is important to pay attention to medication use and dosage in high-AF-risk individuals with hyperuricaemia.

Homocysteine

Elevated levels of Hcy, known as hyperhomocysteinaemia, are linked to an increased risk of cardiovascular diseases and other health issues.⁸⁶ Its prevalence is highly variable worldwide, ranging from 5% to 7% in the general population to 25% among those with vascular diseases.⁸⁷ A meta-analysis of five case-control studies revealed that serum or plasma Hcy levels were significantly higher in AF patients than in control subjects.⁸⁸ For patients with stable angina pectoris in the Norwegian cohort and community participants in the Framingham cohort, a positive association was identified between Hcy levels and the risk of incident AF over a median follow-up of 7.4 and 9.7 years, respectively.⁸⁹ In the age-, sex-, and race-adjusted models, both the Atherosclerosis Risk in Communities study and the Multi-Ethnic Study of Atherosclerosis demonstrated a dose-response relationship between plasma Hcy concentrations and AF incidence. A subsequent meta-analysis of these studies estimated a 27% increased risk of AF for each 1 unit increment in log₂(Hcy) in the fully adjusted model.⁹⁰

While there is a notable association between Hcy levels and AF risk, the precise mechanisms and clinical implications are still being investigated. Elevated Hcy levels are linked to atrial structural remodelling, as indicated by positive correlations with left atrial diameter and markers of collagen Type I degradation^91,92 (Figure 2). Increased Hcy could contribute to electrical remodelling by affecting the function of various ion channels in atrial myocytes, leading to a shortened action potential duration and promoting conditions conducive to AF through pro-arrhythmic effects.⁹³ Furthermore, as a proinflammatory and pro-oxidative marker, Hcy can cause direct biological damage to cardiomyocytes and trigger acute inflammatory responses within the atria.⁹⁴

Several measures are recommended to regulate Hcy levels, including maintaining a diet rich in B vitamins and low in methionine and avoiding smoking and excessive alcohol consumption.⁹⁵ Certain medications, including lipid-lowering drugs and anti-epileptic drugs, can affect Hcy levels and should be considered in the clinical management of hyperhomocysteinaemia.

Adverse conditions or diseases

Depression

Depression is the third leading cause of disability worldwide,⁹⁶ and there were ∼49.4 million DALYs globally in 2020 due to depression.⁹⁷ With the proposed concept of the heart-brain axis, the close relationship between depression and heart conditions has become grounded.^98,99 A Korean cohort with 5 million participants reported that depression was associated with a 25% increased risk of new-onset AF, and those with recurrent episodes of depression had an even greater risk of incident AF (32%).¹⁰⁰ Further research limited the study population to a younger group (aged 20–39 years), which consistently indicated that individuals with depression had a 1.58-fold greater risk of AF.¹⁰¹ Moreover, researchers from Denmark reported an increased risk of AF for antidepressant users, particularly before the initiation of treatment for depression.¹⁰² Overall, meta-analyses also support that depression is one of the emerging risk factors for AF.¹⁰³

The underlying mechanisms explaining the relationship between depression and AF range from unhealthy behaviours to biological risk factors (Figure 3). First, dysfunction of the autonomic nervous system is frequently observed in patients with psychiatric disorders, especially those with depression,¹⁰⁴ which may be due to impaired conduction speed, aggravated cardiac burden, and cardiac electrical remodelling.^105,106 Second, depression is linked to an increase in proinflammatory cytokines, such as interleukin-6 (IL-6) and tumour necrosis factor (TNF)-α,¹⁰⁷ which alter atrial electrophysiology and structural substrates.¹⁰⁸ Third, depression could exacerbate adverse metabolic health factors such as hypertension and obesity and thereby affect AF risk.¹⁰⁹ Moreover, the use of antidepressants may induce AF.¹⁰³ The cardiovascular effect of tricyclic antidepressants may involve a decrease in intraventricular conduction speed, leading to prolonged PR, QRS, and QT intervals.¹¹⁰

Approximately 60% of mental health care treatment occurs in the primary care setting,¹¹¹ and 62% of antidepressant prescriptions are written by general practitioners.¹¹² Therefore, universal screening for depression in all adult patients in the primary care setting has been recommended by the US Preventive Services Task Force.¹¹³

Epilepsy

Epilepsy is one of the most burdensome chronic neurologic disorders, directly affecting ∼45.9 million people worldwide.¹¹⁴ Atrial fibrillation is the most common subtype of arrhythmia in people with epilepsy.¹¹⁵ The prevalence of AF in persons with epilepsy is nearly twice that in persons without epilepsy.¹¹⁶ The results from one retrospective, case-crossover study indicated that epilepsy or status epilepticus encounters had greater odds of subsequent AF events over multiple observation intervals.¹¹⁷ After 329 432 individuals with a median follow-up of 12.5 years were evaluated, the risk of incident AF was found to be 1.26-fold greater in people with epilepsy.¹¹⁸

Intriguingly, the pathophysiological influence of epileptic seizures on AF is conceptualized as ‘the epileptic heart’: electrical and mechanical dysfunction of the heart and coronary vasculature caused by a chronic epilepsy-induced catecholamine surge and sustained hypoxemia¹¹⁹ (Figure 3). In addition to autonomic dysregulation,¹²⁰ stress hormones such as adrenaline and noradrenaline are released during epileptic activity,¹²¹ increasing cardiac excitability. Moreover, epilepsy induces cerebral hypoperfusion and hypoxia, resulting in neuronal injury and potential myocardial ischaemia that aggravate remodelling of atrial tissue, including focal myocardial fibrosis and atrial enlargement.^119,122 Dysfunction of K⁺, Na⁺, and Ca²⁺ channels may be one of the bases of abnormal cardiac electrophysiology altered by chronic epilepsy,^123,124 providing potential intervention targets.

Another aspect to be noted is the pro-arrhythmic effects of some anti-seizure medications.¹²⁵ Medications with sodium channel-blocking properties, such as phenytoin and lamotrigine, have been implicated in QT interval prolongation¹²⁶ and may increase the risk of arrhythmias,¹¹⁸ particularly at higher doses or in patients with pre-existing cardiac conditions. Therefore, anti-epileptic drugs should be prescribed with caution for epilepsy patients with high-risk AF.

Despite the above findings, controlling seizures through medication adherence may still be the cornerstone to reduce the risk of AF by minimizing potential triggers,¹¹⁸ and regular cardiac assessments are another enduring necessity.

Clonal haematopoiesis of indeterminate potential

The presence of age-related pre-leukaemic mutations in healthy individuals, termed CHIP, commonly occurs in 10%–20% of people older than 70 years.¹²⁷ Although CHIP itself does not cause specific symptoms or physical abnormalities, it confers an increased risk of CVD.¹²⁸ The influence of CHIP on AF has only recently been explored. Clonal haematopoiesis of indeterminate potential mutations are 1.4-fold more common in AF patients than in non-AF patients.¹²⁹ One large population-based cohort study revealed that CHIP was independently associated with incident AF (HR 1.11).¹³⁰ Mendelian randomization analyses also suggested the causal role of CHIP in the development of AF.¹³¹

Given that CHIP represents a heterogeneous set of mutations, certain mutations in CHIP may signify a greater risk of incident AF. PPM1D CHIP was found to be the highest-risk subtype for AF,¹³⁰ and TET2^132,133 and DNMT3A^129,132 are two other driver mutations. Inflammation is the most proposed underlying mechanism linking these CHIP mutations and AF. Greater inflammatory responses were observed in CHIP carriers than in non-carriers both pre- and post-operatively.¹³² The specific molecular mechanism can be attributed to the activation of the NLPR3 inflammasome and the IL-1β/IL-6 pathway^133–135 (Figure 3). Animal experiments indicate that increased release of the cytokines IL-1β and IL-6 from TET2-deficient macrophages, which is mediated by NLPR3 inflammasome activation, may result in altered calcium handling and AF propensity.¹³³ Cardiac fibrotic remodelling also partially accounts for the pathology of CHIP in AF, as supported by evidence from both animal and human studies.^130,136,137 For example, large CHIP was associated with myocardial interstitial fibrosis, as assessed by cardiac magnetic resonance.¹³⁰ Further research is warranted to elucidate these processes and identify novel therapeutic targets for AF.

The prevention of CHIP, not only its treatment, is far beyond exploration. Whether cardiovascular health factors can counteract the impact of CHIP on AF needs further study. Hence, the priority strategy falls on regular and long-term cardiac monitoring among individuals at high risk of AF, especially those with large-scale CHIP mutations.

Infections

In the past 5 years, the association between coronavirus disease 2019 (COVID-19) and AF has garnered more attention than other infectious diseases. COVID-19 status was found to have the greatest association with incident AF, rather than with other CVDs, such as heart failure and coronary artery disease.¹³⁸ During COVID-19 infection, the incidence of new-onset AF ranges from 3% to 10% in non-critically ill patients and from 16% to 44% in patients hospitalized in intensive care units.^139,140 Additionally, during the COVID-19 lockdown period in the USA, patients in high COVID-19 states were more affected by AF than were those in lower COVID-19 prevalent states.¹⁴¹ Social disruption could be a potential reason, including staying at home, increased alcohol consumption, depression, loss of employment, and weight gain.¹⁴¹

However, AF is not specific to COVID-19. Compared with inpatients with influenza, patients with COVID-19 had similar¹⁴² or even lower¹⁴³ rates of AF. Infectious diseases, including respiratory infections, infections with Helicobacter pylori, human immunodeficiency virus, and herpes simplex virus, and oral inflammation have all been shown to be related to AF,^144–150 although some associations remain controversial and require further large prospective cohort and mechanistic studies. Notably, patients with pneumonia were found to have the highest odds of developing AF,¹⁴⁵ rather than sepsis, gastrointestinal, or urinary infections. Furthermore, the vulnerability to AF might also be affected by the severity of the infection.¹⁵¹ Since AF can be asymptomatic, for patients with severe infections, especially those with traditional risk factors, intensive screening, and management for complications such as myocarditis may help prevent the development of AF.¹⁵²

Most infections trigger an immune response that leads to the release of proinflammatory cytokines such as IL-6, IL-8, TNF-α, and high-sensitivity C-reactive protein.^108,153 Severe infections can also induce a hypercoagulable state, leading to microthrombi formation in the microvasculature and the induction of localized cardiac ischaemia.¹⁵⁴ In COVID-19 infection, pericytes in cardiac tissues are directly targeted by acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through angiotensin-converting enzyme 2 receptors,¹⁵⁵ leading to increased microvascular permeability, local tissue inflammation, and fibrosis.¹⁵⁶ Electrolyte and autonomic nervous system imbalances caused by infections can alter cardiac electrophysiological properties and reduce variability, creating a pro-arrhythmic environment.¹⁵⁷ For example, post-COVID-19 patients with postural orthostatic tachycardia syndrome, a post-acute sequela characterized by potential autonomic dysfunction,¹⁵⁸ presented prolonged atrial electromechanical delay,¹⁵⁹ which has been found to be closely associated with AF,¹⁶⁰ helping bridge the underlying link between COVID-19 and AF. In addition, pulmonary vascular dysfunction, such as pulmonary hypertension in patients with severe COVID-19, increases right atrial pressure and atrial stretch, resulting in further tissue stiffness.¹⁶¹ Thus, a multifaceted interplay of the above potential mechanisms may jointly contribute to the structural and electrical remodelling of myocardial tissue (Figure 3).

Asthma

In addition to the well-acknowledged risk factor of chronic obstructive pulmonary disease, asthma, another prevalent chronic respiratory disease, has also been increasingly recognized as an important risk factor for AF.¹⁶² It is estimated to affect 262 million people and causes 455 000 deaths worldwide.¹⁶³ A dose–response association was observed between levels of asthma control and risk of AF with the highest HR 1.74 in participants with uncontrolled asthma.¹⁶⁴ This finding was further confirmed by another prospective longitudinal study that persistent asthma was associated with a greater risk for incident AF.¹⁶⁵

Hypoxia is one major pathophysiology linking asthma and AF (Figure 3). Chronic hypoxaemia alters the expression of hypoxia-inducible Factor 1, leading to increased systemic inflammation and oxidative stress.^166,167 Prominent inflammatory responses in asthma, which are, in part, shared with AF, such as the leukotriene receptor pathways, could partially account for the intrinsic interaction.¹⁶⁵ Moreover, the dysfunction of the airway autonomic nervous system may be involved in AF progression.^164,167 Owing to the distribution of β receptors on cardiac muscle, treatments such as short-acting bronchodilator β-agonists may be potential triggers of AF.^165,167 In general, correcting hypoxia, achieving long-term stability, and reducing acute exacerbations may be the primary goals for lowering the risk of AF in patients with asthma.

Environmental factors

Acoustic pollution

With the progress of urbanization and globalization, transportation noise poses an increasing threat to human health, precipitating stress reactions and contributing to CVD.¹⁶⁸ In the Danish Nurse Cohort, two studies reported suggestive evidence between long-term exposure to residential road traffic noise and wind turbine noise and incident AF.^169,170 The estimated risk of AF was 18% and 30% greater in nurses exposed to high-decibel traffic noise and wind turbine noise at night, respectively.^169,170 Monrad et al.¹⁷¹ also reported an association between a 6% greater risk of incident AF and 5 year mean road traffic noise levels prior to diagnosis. However, after adjusting for traffic-related air pollution, the association was attenuated. Researchers have postulated that these associations are difficult to separate from exposure to air pollution.¹⁷¹ Hence, a potential association between noise pollution and AF has been noted, but these links are currently weak and require better-designed experiments.¹⁷²

Mechanistically, noise and noise disturbances act as stressors, activating the autonomic nervous system and promoting the release of stress hormones. This physiological change may induce AF in susceptible individuals. Recent experimental research has shown that aircraft noise is associated with oxidative stress-induced vascular damage, which is mediated by the activation of NADPH oxidase, the uncoupling of endothelial nitric oxide synthase, and the infiltration of inflammatory cells into the vasculature.¹⁷³ In their study on epidemiological noise, Babisch et al.¹⁷⁴ reported greater chronic physiological arousal with higher catecholamine levels in noise-exposed subjects than in those with less exposure, which influenced cardiovascular outcomes. In addition, noise can interfere with sleep and lead to disruption of circadian rhythms, which can affect cardiometabolic health¹⁷⁵ (Figure 4).

To reduce the adverse impact of noise on health, urban planners should prioritize the reduction of noise at the source, invest in alternative means of mobility, and an urban infrastructure that creates positive soundscapes such as tree belts, green walls, green roofs, and more green spaces in cities.

Other environmental factors

It should be noted that the evidence of some notable environmental factors at present is basically cross-sectional or among AF patients; thus, there is no relatively robust evidence for primary prevention. For example, when temperatures decrease, the likelihood of an AF burden/episode increases. Compared with temperatures of 31.5°C, extremely cold conditions (−9.3°C) increase the risk of AF episodes by 25%.¹⁷⁶ Studies from Finland¹⁷⁷ reported a seasonal variation in AF episodes, with the highest risk occurring in the winter. On the other hand, as temperatures exceeded 28°C in early summer, the likelihood of hospitalizations for AF also increased 95%.¹⁷⁸ Although no correlation was found between daily humidity and acute AF emergency visits,¹⁷⁹ among 200 patients with a double-cavity implantable cardioverter defibrillator, each 0.5 g/m³ reduction in absolute humidity within 2 h was associated with a 5% greater odds of paroxysmal AF.¹⁸⁰ Additionally, the participants with the highest tertile of greenness were associated with reduced odds of AF by 6%, although the associations were attenuated after adjusting for biological risk factors.¹⁸¹ Given the limited evidence for primary prevention, further investigations are needed in a large prospective cohort and in the molecular and cellular pathways involved.

Some mechanisms may be involved. Exposure to lower temperatures and reduced-humidity triggers thermoregulatory responses that engage both the sympathetic nervous system and the coagulation cascade.^182,183 Concurrently, there is an elevation in cardiac output to sustain increased metabolic demands associated with thermoregulation.¹⁸³ In addition, an increased presence of tree canopies may enhance shading, thereby making walking and other outdoor activities more appealing as well as engaging in physical activity and/or positive social interaction.¹⁸⁴ Greenness can also contribute to improved health by restoring attention and reducing perceived stress,^185,186 alleviating the effects of air pollution¹⁸⁷, and mitigating urban heat island phenomena.¹⁸⁸

It is crucial for individuals, society, and policy-makers to emphasize environmental action across waste, transportation, energy, education and awareness, community activities, investment, and international policy. For climate change and enhance greenness, we must invest in renewable energy and promote green initiatives to reduce carbon emissions and protect natural ecosystems.

Relationship between non-traditional and traditional risk factors

Studies on AF have revealed a complex relationship between traditional and non-traditional risk factors, indicating that the underlying mechanisms of interaction or mediation may contribute to AF risk. Sex and physical activity, both well-established traditional risk factors for AF, interact with night shift work. Women with more than 10 years of night shift work and individuals reporting non-ideal physical activity with a high frequency of night shifts display a significantly increased AF risk, but these effects were not observed among men or those with ideal physical activity.³⁶ Moreover, E. ramulus was found to mediate 8.05% of the relationship between coronary artery disease and AF risk, whereas the genus Holdemania mediated 12.01% of the association between body mass index and AF risk.⁷⁴ Therefore, understanding these interactions or mediating effects between risk factors is crucial for developing comprehensive strategies for AF prevention, highlighting the need for an integrated approach that addresses both traditional and emerging risk factors.

Potential mitigation strategies

Therapeutic strategies against important traditional risk factors such as obesity, hypertension, diabetes, and sleep apnoea have been developed. However, the global prevalence of AF and associated DALYs continues to rapidly increase.³ This phenomenon further highlights the need to address the underestimation of non-traditional determinants of AF, especially in vulnerable individuals with existing traditional risk factors. Table 2 offers a compilation of organizations, essential preventative measures, guidelines, and resources, targeting non-traditional risk factors, which can serve as references for further insight and action.

Limitations

First, our definition of ‘non-traditional risk factors’ has its subjectivity. Currently, some so-called traditional factors based on our definition may still be considered non-traditional, such as air pollution and other newly added factors in the guidelines. Thus, the concept ‘non-traditional’ changes with time. Second, the non-systematic nature of the literature search may introduce bias and risk overlooking other additional risk factors. We acknowledge that this exploration cannot encompass every potential factor and reflects the findings available up to this point. While these limitations are inherent to the current search, they also provide opportunities for future research and further exploration in this area.

Conclusions

A growing number of studies have explored non-traditional risk factors for AF. We presented those discovered in studies with prospective designs and large sample sizes. These factors include poor lifestyle factors, novel biomarkers, adverse conditions or diseases, and environmental factors. Prospective studies provide unique insights into these risk factors and their associations with AF, enabling improved risk stratification. These data, as well as data from experimental investigations, provide a consistent, actionable body of evidence supporting the benefits of controlling these non-traditional risk factors. Nonetheless, further evidence from larger and more diverse populations, as well as experimental trials, is necessary to substantiate their impact on or causal relationship with AF, which is crucial for advocating for updates to AF prevention guidelines. Moreover, healthcare providers and public health organizations should recognize the necessity of early detection and intervention for emerging adverse factors for AF within the context of a rapidly changing society.

Acknowledgements

We are grateful to Dr Bin Wang and Dr Jiang Li from the Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, for their valuable suggestions during the revision of this manuscript.

Supplementary data

Supplementary data are not available at European Heart Journal online.

Declarations

Disclosure of Interest

All authors declare no disclosure of interest for this contribution.

Data Availability

No data were generated or analysed for this manuscript.

Funding

N.W. is supported by the National Natural Science Foundation of China (82170870, 82370862), the Shanghai Municipal Health Commission (2022XD017), and the Shanghai Municipal Human Resources and Social Security Bureau (2020074). P.S. is supported by an Investigator Grant Fellowship from the National Health and Medical Research Council of Australia.

References

Author notes