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Age Modified Relationship Between Modifiable Risk Factors and the Risk of Atrial Fibrillation

2021; Lippincott Williams & Wilkins; Volume: 15; Issue: 1 Linguagem: Inglês

10.1161/circep.121.010409

1941-3149

Satoshi Matsuoka, Hidehiro Kaneko, Akira Okada, Kojiro Morita, Hidetaka Itoh, Nobuaki Michihata, Taisuke Jo, Norifumi Takeda, Hiroyuki Morita, Katsuhito Fujiu, Sunao Nakamura, Koichi Node, Hideo Yasunaga, Issei Komuro,

Cardiac electrophysiology and arrhythmias

HomeCirculation: Arrhythmia and ElectrophysiologyVol. 15, No. 1Age Modified Relationship Between Modifiable Risk Factors and the Risk of Atrial Fibrillation Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyRedditDiggEmail Jump toFree AccessLetterPDF/EPUBAge Modified Relationship Between Modifiable Risk Factors and the Risk of Atrial Fibrillation Satoshi Matsuoka, MD, Hidehiro Kaneko, MD, Akira Okada, MD, Kojiro Morita, PhD, Hidetaka Itoh, MD, Nobuaki Michihata, MD, Taisuke Jo, MD, Norifumi Takeda, MD, Hiroyuki Morita, MD, Katsuhito Fujiu, MD, Sunao Nakamura, MD, Koichi Node, MD, Hideo Yasunaga, MD and Issei Komuro, MD Satoshi MatsuokaSatoshi Matsuoka https://orcid.org/0000-0003-3642-2603 The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. The Department of Cardiology, New Tokyo Hospital, Matsudo, Japan (S.M., S.N.). , Hidehiro KanekoHidehiro Kaneko Correspondence to: Hidehiro Kaneko, MD, PhD, The Department of Cardiovascular Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. Email E-mail Address: [email protected] https://orcid.org/0000-0003-2553-6170 The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. The Department of Advanced Cardiology (H.K., K.F.), The University of Tokyo, Tokyo, Japan. , Akira OkadaAkira Okada https://orcid.org/0000-0001-6480-3388 Department of Prevention of Diabetes and Lifestyle-Related Diseases, Graduate School of Medicine (A.O.), The University of Tokyo, Tokyo, Japan. , Kojiro MoritaKojiro Morita Global Nursing Research Center, Graduate School of Medicine (K.M.), The University of Tokyo, Tokyo, Japan. , Hidetaka ItohHidetaka Itoh https://orcid.org/0000-0001-6610-6201 The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. , Nobuaki MichihataNobuaki Michihata https://orcid.org/0000-0003-3091-114X The Department of Health Services Research (N.M., T.J.), The University of Tokyo, Tokyo, Japan. , Taisuke JoTaisuke Jo https://orcid.org/0000-0002-8503-022X The Department of Health Services Research (N.M., T.J.), The University of Tokyo, Tokyo, Japan. , Norifumi TakedaNorifumi Takeda https://orcid.org/0000-0003-4818-3347 The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. , Hiroyuki MoritaHiroyuki Morita The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. , Katsuhito FujiuKatsuhito Fujiu https://orcid.org/0000-0002-1889-9291 The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. The Department of Advanced Cardiology (H.K., K.F.), The University of Tokyo, Tokyo, Japan. , Sunao NakamuraSunao Nakamura https://orcid.org/0000-0002-0651-0090 The Department of Cardiology, New Tokyo Hospital, Matsudo, Japan (S.M., S.N.). , Koichi NodeKoichi Node https://orcid.org/0000-0002-2534-0939 Department of Cardiovascular Medicine, Saga University, Saga, Japan (K.N.). , Hideo YasunagaHideo Yasunaga https://orcid.org/0000-0002-6017-469X The Department of Clinical Epidemiology and Health Economics, School of Public Health (H.Y.), The University of Tokyo, Tokyo, Japan. and Issei KomuroIssei Komuro https://orcid.org/0000-0002-0714-7182 The Department of Cardiovascular Medicine (S.M., H.K., H.I., N.T., H.M., K.F., I.K.), The University of Tokyo, Tokyo, Japan. Originally published23 Dec 2021https://doi.org/10.1161/CIRCEP.121.010409Circulation: Arrhythmia and Electrophysiology. 2022;15:e010409Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: December 23, 2021: Ahead of Print Atrial fibrillation (AF) is one of the most common cardiac arrhythmias and increases the risk of stroke, heart failure, and mortality. Although AF predominantly occurs in older people, it could also affect younger generation. Considering that both aging and modifiable risk factors such as obesity, hypertension, and diabetes are major risk factors for AF, the influence of modifiable risk factors on the development of AF would be greater in younger people than in older people. In this study, we examined the age-dependent relationship between each component of modifiable risk factors and incident AF.This is an observational cohort study using the JMDC Claims Database, which is a large-scale claims database in Japan,1 between January 2005 and April 2020. Of the records of 3 380 711 individuals with available health checkup data, we excluded individuals aged <20 years (n=21 022), those with a history of cardiovascular disease including AF (n=162 245), those with missing data on medications, cigarette smoking, alcohol consumption, and physical inactivity (n=600 003), leaving a final analytic sample of 2 597 441 participants.This study was conducted in accordance with the guidelines of the Ethical Committee of the University of Tokyo (2018-10862), the Declaration of Helsinki, and the Transparency and Openness Promotion Guideline. The requirement for informed consent was waived because all data from the JMDC Claims Database were deidentified. The JMDC Claims Database is available for purchase from JMDC, Inc.We defined obesity, high waist circumference, hypertension, diabetes, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity as previously described.2,3 The primary outcome was AF using the International Classification of Diseases, Tenth Revision codes collected between January 2005 and April 2020.1 We conducted multivariable Cox regression analyses to identify the determinants of AF in each age category (20–49 years, 50–59 years, and 60–75 years). The P values for the interactions between the three age categories were calculated in a multivariable model. We estimated the relative risk reduction of each risk factor based on hazard ratios. The discriminative ability of a model, including age, sex, obesity, high waist circumference, hypertension, diabetes, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity among each age category group, was assessed using Harrell C statistic. A P value of <0.05, was considered statistically significant. Statistical analyses were performed using SPSS and STATA.Study participants were categorized as aged 20 to 49 years (n=1 676 217), 50 to 59 years (n=639 648), and 60 to 75 years (n=281 576). During a mean follow-up of 3.3±2.5 years, 12 773 AF events were recorded. The event rate for AF events was the lowest in participants aged 20 to 49 years (7.8 [95% CI, 7.6–8.0] per 10 000 person-year), followed by those aged 50 to 59 years (22.8 [95% CI, 22.2–23.4] per 10 000 person-year) and those aged 60 to 75 years (45.8 [95% CI, 44.3–47.3] per 10 000 person-year).Age, male sex, high waist circumference, hypertension, and alcohol consumption were associated with a higher incidence of AF in all age categories. Concordant with a previous study,4 dyslipidemia was associated with a lower incidence of AF in all age categories. Hazard ratios for obesity, high waist circumference, hypertension, diabetes, and dyslipidemia decreased with age. P values for interaction were significant for sex, hypertension, and diabetes (Figure [A]). There was a trend that obesity, high waist circumference, hypertension, and diabetes conferred a greater relative risk reduction in younger people than in older people (Figure [B]). The C statistics of the aforementioned model were 0.69 (95% CI, 0.68–0.70), 0.68 (95% CI, 0.67–0.69), and 0.66 (95% CI, 0.65–0.67) in participants aged 20 to 49 years, 50 to 59 years, and 60 to 75 years, respectively.Download figureDownload PowerPointFigure. Age-dependent Association of modifiable risk factors with risk of developing atrial fibrillation. We performed multivariable Cox regression analysis including age, sex, obesity, high waist circumference, hypertension, diabetes, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity to determine the relationship of risk factors with incident atrial fibrillation (A). Relative risk reduction of obesity, high waist circumference, hypertension, diabetes, dyslipidemia, cigarette smoking, alcohol consumption, and physical inactivity for atrial fibrillation was summarized (B).To the best of our knowledge, this is the first large-scale study demonstrating that modifiable risk factors would afford a higher proportion of risk in younger people than in older people. However, we need to consider several limitations. Recorded diagnoses of administrative databases are generally considered less well-validated. Because the JMDC Claims Database mainly included employed working-age people in Japan, it is not easy to expand our results to other population (eg, outside of Japan). Detection bias may cause overestimation or underestimation of the true relationship between risk factors and incident AF. There could be unmeasured confounders and residual bias even after multivariable Cox regression analyses. Although we compared the association of risk factors with incident AF between age groups, the difference in the response to treatment for these risk factors among age groups was not investigated.In conclusion, despite a lower incidence of AF in younger participants than in older participants, the contribution of modifiable risk factors to the development of future AF would be greater in younger participants than in older participants. Although risk factor modification is important across the life course, efforts for the optimization of risk factors in younger people would be more beneficial than in older people for the primary prevention of AF.Article InformationSources of FundingThis work was supported by Grants from the Ministry of Health, Labour and Welfare, Japan (19AA2007 and H30-Policy-Designated-004) and the Ministry of Education, Culture, Sports, Science and Technology, Japan (17H04141).DisclosuresResearch funding and scholarship funds (Drs Kaneko and Fujiu) from Medtronic Japan, Boston Scientific Japan, Biotronik Japan, Simplex QUANTUM, and Fukuda Denshi. The other authors report no conflicts.FootnotesFor Sources of Funding and Disclosures, see page 67.Correspondence to: Hidehiro Kaneko, MD, PhD, The Department of Cardiovascular Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. Email [email protected]ac.jpReferences1. Kaneko H, Yano Y, Itoh H, Morita K, Kiriyama H, Kamon T, Fujiu K, Michihata N, Jo T, Takeda N, et al.. Association of blood pressure classification using the 2017 American College of Cardiology/American Heart Association Blood Pressure Guideline With Risk of Heart Failure and Atrial Fibrillation.Circulation. 2021; 143:2244–2253. doi: 10.1161/CIRCULATIONAHA.120.052624LinkGoogle Scholar2. Kaneko H, Itoh H, Yotsumoto H, Kiriyama H, Kamon T, Fujiu K, Morita K, Michihata N, Jo T, Morita H, et al.. Association of body weight gain with subsequent cardiovascular event in non-obese general population without overt cardiovascular disease.Atherosclerosis. 2020; 308:39–44. doi: 10.1016/j.atherosclerosis.2020.05.015CrossrefMedlineGoogle Scholar3. Kaneko H, Itoh H, Kamon T, Fujiu K, Morita K, Michihata N, Jo T, Morita H, Yasunaga H, Komuro I. Association of cardiovascular health metrics with subsequent cardiovascular disease in young adults.J Am Coll Cardiol. 2020; 76:2414–2416. doi: 10.1016/j.jacc.2020.09.545CrossrefMedlineGoogle Scholar4. Lopez FL, Agarwal SK, Maclehose RF, Soliman EZ, Sharrett AR, Huxley RR, Konety S, Ballantyne CM, Alonso A. Blood lipid levels, lipid-lowering medications, and the incidence of atrial fibrillation: the atherosclerosis risk in communities study.Circ Arrhythm Electrophysiol. 2012; 5:155–162. doi: 10.1161/CIRCEP.111.966804LinkGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetails January 2022Vol 15, Issue 1Article InformationMetrics © 2022 American Heart Association, Inc.https://doi.org/10.1161/CIRCEP.121.010409PMID: 34939429 Originally publishedDecember 23, 2021 KeywordsAtrial fibrillationagemortalityrisk factorheart failurePDF download Advertisement SubjectsEpidemiology