Trends and Predictions of Metabolic Risk Factors for Acute Myocardial Infarction: Findings from a Multiethnic Nationwide Cohort

Overview

Journal Lancet Reg Health West Pac

Date 2023 Sep 11

PMID 37693863

Authors

Nicholas W S Chew

Bryan Chong

Si Min Kuo

Jayanth Jayabaskaran

Mingshi Cai

Huili Zheng

Rachel Goh

Gwyneth Kong

Yip Han Chin

Syed Saqib Imran

Michael Liang

Patrick Lim

Thon Hon Yong

Boon Wah Liew

Pow Li Chia

Hee Hwa Ho

David Foo

Deanna Khoo

Zijuan Huang

Terrance Chua

Jack Wei Chieh Tan

Khung Keong Yeo

Derek Hausenloy

Hui Wen Sim

Jieli Kua

Koo Hui Chan

Poay Huan Loh

Toon Wei Lim

Adrian F Low

Ping Chai

Chi Hang Lee

Tiong Cheng Yeo

James Yip

Huay Cheem Tan

Mamas A Mamas

Stephen J Nicholls

Mark Y Chan

Affiliations

Soon will be listed here.

Abstract

Background: Understanding the trajectories of metabolic risk factors for acute myocardial infarction (AMI) is necessary for healthcare policymaking. We estimated future projections of the incidence of metabolic diseases in a multi-ethnic population with AMI.

Methods: The incidence and mortality contributed by metabolic risk factors in the population with AMI (diabetes mellitus [T2DM], hypertension, hyperlipidemia, overweight/obesity, active/previous smokers) were projected up to year 2050, using linear and Poisson regression models based on the Singapore Myocardial Infarction Registry from 2007 to 2018. Forecast analysis was stratified based on age, sex and ethnicity.

Findings: From 2025 to 2050, the incidence of AMI is predicted to rise by 194.4% from 482 to 1418 per 100,000 population. The largest percentage increase in metabolic risk factors within the population with AMI is projected to be overweight/obesity (880.0% increase), followed by hypertension (248.7% increase), T2DM (215.7% increase), hyperlipidemia (205.0% increase), and active/previous smoking (164.8% increase). The number of AMI-related deaths is expected to increase by 294.7% in individuals with overweight/obesity, while mortality is predicted to decrease by 11.7% in hyperlipidemia, 29.9% in hypertension, 32.7% in T2DM and 49.6% in active/previous smokers, from 2025 to 2050. Compared with Chinese individuals, Indian and Malay individuals bear a disproportionate burden of overweight/obesity incidence and AMI-related mortality.

Interpretation: The incidence of AMI is projected to continue rising in the coming decades. Overweight/obesity will emerge as fastest-growing metabolic risk factor and the leading risk factor for AMI-related mortality.

Funding: This research was supported by the NUHS Seed Fund (NUHSRO/2022/058/RO5+6/Seed-Mar/03) and National Medical Research Council Research Training Fellowship (MOH-001131). The SMIR is a national, ministry-funded registry run by the National Registry of Diseases Office and funded by the Ministry of Health, Singapore.

Citing Articles

A sex-disaggregated analysis of the prognostic value of lean type 2 diabetes mellitus in the adult population with acute myocardial infarction.

Kong G, Koh J, Chia J, Neo B, Chen Y, Cao G Cardiovasc Diabetol. 2025; 24(1):59.

PMID: 39920748 PMC: 11806904. DOI: 10.1186/s12933-024-02552-0.

Cohort profile: AI-driven national Platform for CCTA for clinicaL and industriaL applicatiOns (APOLLO).

Baskaran L, Leng S, Dutta U, Teo L, Yew M, Sia C BMJ Open. 2024; 14(12):e089047.

PMID: 39622571 PMC: 11624714. DOI: 10.1136/bmjopen-2024-089047.

The burden of cardiovascular disease in Asia from 2025 to 2050: a forecast analysis for East Asia, South Asia, South-East Asia, Central Asia, and high-income Asia Pacific regions.

Goh R, Chong B, Jayabaskaran J, Jauhari S, Chan S, Kueh M Lancet Reg Health West Pac. 2024; 49:101138.

PMID: 39100533 PMC: 11296249. DOI: 10.1016/j.lanwpc.2024.101138.

Predicted but not destined: considerations for obesity-related cardiovascular risk projection.

Wang T, Hung C, Yeh H Lancet Reg Health West Pac. 2023; 37:100828.

PMID: 37693872 PMC: 10485665. DOI: 10.1016/j.lanwpc.2023.100828.

References

. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363(9403):157-63. DOI: 10.1016/S0140-6736(03)15268-3. View

Marcassa C, Giordano A, Giannuzzi P . Five-year hospitalisations and survival in patients admitted to inpatient cardiac rehabilitation after cardiac surgery. Eur J Prev Cardiol. 2016; 23(15):1609-17. DOI: 10.1177/2047487316655452. View

Myint P, Kwok C, Luben R, Wareham N, Khaw K . Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease. Heart. 2014; 100(20):1613-9. DOI: 10.1136/heartjnl-2014-305816. View

Ward Z, Bleich S, Cradock A, Barrett J, Giles C, Flax C . Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity. N Engl J Med. 2019; 381(25):2440-2450. DOI: 10.1056/NEJMsa1909301. View

Nowakowska M, Zghebi S, Ashcroft D, Buchan I, Chew-Graham C, Holt T . The comorbidity burden of type 2 diabetes mellitus: patterns, clusters and predictions from a large English primary care cohort. BMC Med. 2019; 17(1):145. PMC: 6659216. DOI: 10.1186/s12916-019-1373-y. View

Peters S, Bots S, Woodward M . Sex Differences in the Association Between Measures of General and Central Adiposity and the Risk of Myocardial Infarction: Results From the UK Biobank. J Am Heart Assoc. 2018; 7(5). PMC: 5866342. DOI: 10.1161/JAHA.117.008507. View

Chew N, Ng C, Muthiah M, Sanyal A . Comprehensive Review and Updates on Holistic Approach Towards Non-Alcoholic Fatty Liver Disease Management with Cardiovascular Disease. Curr Atheroscler Rep. 2022; 24(7):515-532. DOI: 10.1007/s11883-022-01027-5. View

Ayyoubzadeh S, Ayyoubzadeh S, Zahedi H, Ahmadi M, Niakan Kalhori S . Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study. JMIR Public Health Surveill. 2020; 6(2):e18828. PMC: 7159058. DOI: 10.2196/18828. View

Porhcisaliyan V, Wang Y, Tan N, Jafar T . Socioeconomic status and ethnic variation associated with type 2 diabetes mellitus in patients with uncontrolled hypertension in Singapore. BMJ Open Diabetes Res Care. 2021; 9(1). PMC: 8728350. DOI: 10.1136/bmjdrc-2020-002064. View

10.

Arnett D, Blumenthal R, Albert M, Buroker A, Goldberger Z, Hahn E . 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2019; 74(10):e177-e232. PMC: 7685565. DOI: 10.1016/j.jacc.2019.03.010. View

11.

Lee E, Chew N, Ng P, Yeo T . A spectrum of cardiac manifestations post Pfizer-BioNTech COVID-19 vaccination. QJM. 2021; 114(9):661-662. DOI: 10.1093/qjmed/hcab177. View

12.

Tai E, Chia B, Bastian A, Chua T, Ho S, Koh T . Ministry of Health Clinical Practice Guidelines: Lipids. Singapore Med J. 2017; 58(3):155-166. DOI: 10.11622/smedj.2017018. View

13.

Loh J, Tan L, Zheng H, Lau Y, Chan S, Tan K . First Medical Contact-to-Device Time and Heart Failure Outcomes Among Patients Undergoing Primary Percutaneous Coronary Intervention. Circ Cardiovasc Qual Outcomes. 2018; 11(8):e004699. DOI: 10.1161/CIRCOUTCOMES.118.004699. View

14.

Grundy S, Stone N, Bailey A, Beam C, Birtcher K, Blumenthal R . 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2018; 139(25):e1082-e1143. PMC: 7403606. DOI: 10.1161/CIR.0000000000000625. View

15.

Tan C, Tai E, Tan C, Chia K, Lee J, Chew S . APOE polymorphism and lipid profile in three ethnic groups in the Singapore population. Atherosclerosis. 2003; 170(2):253-60. DOI: 10.1016/s0021-9150(03)00232-6. View

16.

Kong G, Chew N, Ng C, Chin Y, Lim O, Ambhore A . Prognostic Outcomes in Acute Myocardial Infarction Patients Without Standard Modifiable Risk Factors: A Multiethnic Study of 8,680 Asian Patients. Front Cardiovasc Med. 2022; 9:869168. PMC: 9001931. DOI: 10.3389/fcvm.2022.869168. View

17.

Tang A, Ng C, Phang P, Chan K, Chin Y, Fu C . Comparative Burden of Metabolic Dysfunction in Lean NAFLD vs Non-lean NAFLD - A Systematic Review and Meta-analysis. Clin Gastroenterol Hepatol. 2022; 21(7):1750-1760.e12. DOI: 10.1016/j.cgh.2022.06.029. View

18.

Lin G, Xinhe Z, Haoyu T, Xing J, Dan L, Ningning W . Epidemiology and lifestyle survey of non-alcoholic fatty liver disease in school-age children and adolescents in Shenyang, Liaoning. BMC Pediatr. 2022; 22(1):286. PMC: 9112471. DOI: 10.1186/s12887-022-03351-w. View

19.

Taylor R, Dalal H, Zwisler A . Cardiac rehabilitation for heart failure: 'Cinderella' or evidence-based pillar of care?. Eur Heart J. 2023; 44(17):1511-1518. PMC: 10149531. DOI: 10.1093/eurheartj/ehad118. View

20.

Chew N, Sia C, Wee H, Benedict L, Rastogi S, Kojodjojo P . Impact of the COVID-19 Pandemic on Door-to-Balloon Time for Primary Percutaneous Coronary Intervention　- Results From the Singapore Western STEMI Network. Circ J. 2020; 85(2):139-149. DOI: 10.1253/circj.CJ-20-0800. View