Factors Associated With Return to Work After Acute Myocardial Infarction in China

Zihan Jiang; Rachel P Dreyer; John A Spertus; Frederick A Masoudi; Jing Li; Xin Zheng; Xi Li; Chaoqun Wu; Xueke Bai; Shuang Hu; Yun Wang; Harlan M Krumholz; Hong Chen

doi:10.1001/jamanetworkopen.2018.4831

. 2018 Nov 21;1(7):e184831. doi: 10.1001/jamanetworkopen.2018.4831

Factors Associated With Return to Work After Acute Myocardial Infarction in China

Zihan Jiang ¹, Rachel P Dreyer ^2,³, John A Spertus ^4,⁵, Frederick A Masoudi ^6,⁷, Jing Li ⁸, Xin Zheng ⁸, Xi Li ⁸, Chaoqun Wu ⁸, Xueke Bai ⁸, Shuang Hu ⁸, Yun Wang ^3,⁹, Harlan M Krumholz ^3,^10,¹¹, Hong Chen ^12,^✉, for the China Patient-centered Evaluative Assessment of Cardiac Events (PEACE) Collaborative Group

¹Health Care and International Medical Services, Peking Union Medical College Hospital, Beijing, People’s Republic of China

²Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut

³Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, New Haven, Connecticut

⁴Department of Biomedical and Health Informatics, University of Missouri–Kansas City

⁵Department of Cardiovascular Research, St Luke’s Mid America Heart Institute, Kansas City, Missouri

⁶Department of Medicine, University of Colorado School of Medicine at the Anschutz Medical Campus, Aurora

⁷Colorado Cardiovascular Outcomes Research Consortium, Denver

⁸National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China

⁹Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts

¹⁰Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut

¹¹Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut

¹²Department of Cardiology, Peking University People’s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Beijing, People’s Republic of China

Accepted for Publication: September 26, 2018.

Published: November 21, 2018. doi:10.1001/jamanetworkopen.2018.4831

^✉

Corresponding Author: Hong Chen, MD, Department of Cardiology, Peking University People’s Hospital, Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Beijing, 100044, People’s Republic of China (chenhongbj@medmail.com.cn).

Author Contributions: Drs Hu and Wang had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Krumholz and Chen are co–senior authors.

Concept and design: Jiang, Dreyer, Spertus, Masoudi, J. Li, Wang, Chen.

Acquisition, analysis, or interpretation of data: Jiang, Spertus, Masoudi, J. Li, Zheng, X. Li, Wu, Bai, Hu, Wang, Krumholz.

Drafting of the manuscript: Jiang, Dreyer, Spertus, Chen.

Critical revision of the manuscript for important intellectual content: Jiang, Dreyer, Masoudi, J. Li, Zheng, X. Li, Wu, Bai, Hu, Wang, Krumholz, Chen.

Statistical analysis: Jiang, X. Li, Wang.

Obtained funding: Spertus.

Administrative, technical, or material support: Jiang, Dreyer, Spertus, J. Li, X. Li, Chen.

Supervision: Spertus, J. Li, Krumholz, Chen.

Conflict of Interest Disclosures: Dr Spertus reported being supported by grants from Gilead, Genentech, Lilly, Amorcyte, and EvaHeart; and having a patent for the Seattle Angina Questionnaire with royalties paid. Dr Krumholz reported being a recipient of research agreements from Medtronic and Johnson & Johnson (Janssen), through Yale University, to develop methods of clinical trial data sharing; being the recipient of a grant from the US Food and Drug Administration and Medtronic to develop methods for postmarket surveillance of medical devices; working under contract with the Centers for Medicare & Medicaid Services to develop and maintain performance measures; serving as chair of a cardiac scientific advisory board for UnitedHealth; serving as a participant/participant representative of the IBM Watson Health Life Sciences Board; and being the founder of Hugo, a personal health information platform. No other disclosures were reported.

Funding/Support: This project was supported by grants 2017YFC1310803 and 2017YFC1310801 from the National Key Research and Development Program from the Ministry of Science and Technology of China; grants 2017-I2M-2-002, 2017-I2M-B&R-02, 2016-I2M-1-006, and 2016-I2M-2-004 from the CAMS Innovation Fund for Medical Science; grant 201502009 from the Research Special Fund for Public Welfare Industry of Health from the National Health Commission of China; and grants 81470473 and 81770356 from the National Natural Science Foundation of China.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: The China Patient-centered Evaluative Assessment of Cardiac Events (PEACE) Collaborative Group members are as follows: Jianchang Wang, Congchun Huang, and Haitao Zhang (Air Force General Hospital, Chinese People’s Liberation Army, Beijing Beijing); Likun Ma, Hao Hu, and Xiangyong Kong (Anhui Provincial Hospital, Anhui Hefei); Ruiping Zhao, Wei Du, and Hongyu Li (Baotou Central Hospital, Baotou, Inner Mongolia); Xinchun Yang, Mullei Chen, Xiaotao Zhao, and Zhiyong Zhang (Beijing Chao-Yang Hospital, Capital Medical University Beijing, Beijing); Ping Yang, Zhaohui Fen, Cuiying Mao, and Bing Li (China-Japan Union Hospital of Jilin University, Jilin Changchun); Wei Liu, Wen Cui, Xiaoxin Li, and Yanbin Zhang (Dongfeng County Hospital, Jilin Dongfeng); Feng Wang, Sizhao Li, and Qun Luo (Feng County People’s Hospital, Jiangsu Feng); Qinghua Han, Liqin Duan, and Chunrong Jin (First Hospital of Shanxi Medical University, Shanxi Taiyuan); Yansong Guo, Feng Lin, and Xinjing Chen (Fujian Provincial Hospital, Fujian Fuzhou); Hongtao Pan, Lei Sun, and Peng Gao (General Hospital of China FAW Group Corporation, Jilin Changchun); Wei Zhang, Shuyun Xie, Yanni Zhuang, and Wei Li (Guilin People’s Hospital, Guangxi Guilin); Zhiping Ge, Huihua Wen, Qiaoling Liu, and Yongdong Li (Inner Mongolia Baogang Hospital, Baotou Inner Mongolia); Lang Hong, Linfeng Li, Lihua Yuan, and Yun Li (Jiangxi Provincial People’s Hospital, Jiangxi Nanchang); Peihua Zhao, Jingsheng Sun, and Rengui Chai (Jinghai County Hospital, Tianjin Tianjin); Danbing Zhou, Tongbao Sang, and Dongxue Song (Kuandian Manchu Autonomous County Central Hospital, Liaoning Kuandian); Xu Jiang, Guohao Xu, Yanrong Song, and Hui Liu (Laixi People’s Hospital, Shangdong Laixi); Keyong Shang, Changjiang Liu, Kuituan Xi, and Ying Yu (Laoting County Hospital, Hebei Laoting); Kelian Xu, Cunqi Wang, and Yongan Qian (Lujiang County People’s Hospital, Anhui Lujiang); Ying Yang, Jianbin Huang, and Er Zhu (Minhou County Hospital, Fujian Minhou); Shouzhong Yang, Yudong Li, Jianbu Gao, and Songyu Zhang (Nanyang Central Hospital, Henan Nanyang); Tianhu Liu, Mingjun Yan, and Zhaoping Yu (Pi County People’s Hospital, Sichuang Pi); Xia Wu, Penghui Yang, and Fang Liu (Port Hospital of Hebei Port Group Company, Ltd Hebei); Ying Yang, Guixin Wu, Jiajia Mao, and Cheng Zheng (Qingdao Fuwai Hospital, Shandong Qingdao); Huiping Bian, Bo Chen, and Jiandong Cao (Qinghai Cardiovascular and Cerebrovascular Hospital, Qinghai Xining); Hua Yan, Liyuan Chen, Qiuxia Liu, and Lin Chen (Qinzhou Second People’s Hospital, Guangxi Qinzhou); Xiwu Wang, Zhenlin Wu, Qiang Wang, and Zhaohui Shangguan (Quwo County People’s Hospital, Shanxi Quwo); Bao Li, Bin Yang, Jianhua Li, and Jianhong Wang (Shanxi Cardiovascular Hospital, Shanxi Taiyuan); Yaling Han, Xiaozeng Wang, and Haiwei Liu (Shenyang Northern Hospital, Liaoning Shenyang); Cheng Zhang, Aiguo Sun, and Lijuan Gao (Shuangcheng People’s Hospital, Heilongjiang Shuangcheng); Feng Liu, Xiangfei Meng, Bo Shao, and Zhanling Liao (Shanghai Jiao Tong University School of Medicine, Jiangsu Suzhou); Changyong Zhou, Yini Wang, and Tao Yu (The Affiliated Hospital of Qingdao University, Shandong Qingdao); Jinxiu Lin, Dajun Chai, and Wenxiang Zhao (The First Affiliated Hospital of Fujian Medical University, Fujian Fuzhou); Luoyang Pingshuan Dong, Laijing Du, and Ximei Fan (The First Affiliated Hospital of Henan University of Science & Technology, Henan); Yang Zheng, Zhaoxi Liu, Wenqian Zhou, and Lin Zou (The First Hospital of Jilin University, Jilin Changchun); Yuanzhe Jin, Xiaohong Zhang, and Xueying Zhang (The Fourth Affiliated Hospital of China Medical University, Liaoning Shenyang); Chunxi Cha, Ren Luo, Min Tian, and Juan Ren (The Fourth Affiliated Hospital of Shihezi University & First Division Hospital of the Xinjiang Production and Construction Corps, Xinjiang Akesu); Yongbo Lin, Lin Xu, and Ling Zhou (The People’s Hospital of Dongxihu District of Wuhan, Hubei Wuhan); Zhanquan Li, Ying Liu, Qian Yu, and Yan Xing (The People’s Hospital of Liaoning Province, Liaoning Shenyang); Yuanming Yi, Guanhong Wu, and Xuelian Deng (The People’s Hospital of Wuchuan, Guangdong Wuchuan); Bo Yu, Shuo Zhang, and Shuang Yang (The Second Affiliated Hospital of Harbin Medical University, Heilongjiang); Weiheng Wu, Li Li, and Jianqi Feng (The Second Affiliated Hospital of Xuzhou Medical College, Jiangsu Xuzhou); Xianen Fa, Lihua Zhang, Liqiang Sun, and Lei Liu (The Second Affiliated Hospital of Zhengzhou University, Henan Zhenzhou); Peng Qu, Hongyan Wang, Dayuan Lou, and Dajun Yuan (The Second Hospital of Dalian Medical University, Liaoning Dalian); Zheng Wan, Yuemin Sun, and Bo Bina (Tianjin Medical University General Hospital, Tianjin Tianjing); Xi Su, Songzhi Zhao, Wei Wu, and Yujing Fan (Wuhan Asia Heart Hospital, Hubei Wuhan); Jianye Fu, Fuqin Han, and Yunmei Wang (Wulate County People’s Hospital, Wulate, Inner Mongolia); He Huang, Jianping Zeng, Mingxing Wu, and Yi Zhou (Xiangtan Central Hospital, Hubei Xiangtan); Fusheng Zhao, Xiao Wang, and Guangming Yang (Xinmi First People’s Hospital, Henan Xinmi); Bo Jiang, Liwei Qi, and Tongying Li (Xinmin People’s Hospital, Liaoning Xinmin); Qiang Fu, Zhenyong Li, Peng Wei, and Yi Lu (Xuzhou Central Hospital, Jiangsu Xuzhou); Hongju Zhang, Liuxiao Jun, Ming Hu, and Wei Li (Xuzhou First People’s Hospital, Jiangsu Xuzhou); Qingdong Liu, Qingquan Yang, and Jide Wu (You County People’s Hospital, Hunan Youxian); and Lin Zhang, Yumei Guo, and Huiling Sun (Zhengzhou Central Hospital, Henan Zhengzhou).

Additional Contributions: We thank the hospitals that participated in the China PEACE Prospective Study of Acute Myocardial Infarction for their contributions to this work. We are grateful for the support provided by the Chinese government.

^✉

Corresponding author.

PMCID: PMC6324382 PMID: 30646375

Abstract

Importance

Return to work is an important indicator of recovery after acute myocardial infarction. Little is known, however, about the rate of returning to work within the year after an acute myocardial infarction in China, as well as the factors associated with returning to work after an acute myocardial infarction.

Objectives

To determine the rate of return to work within 12 months after acute myocardial infarction, classify the reasons why patients did not return to work, and identify patient factors associated with returning to work.

Design, Setting, and Participants

This prospective cohort study, conducted in 53 hospitals across 21 provinces in China, identified 1566 patients who were employed at the time of the index acute myocardial infarction hospitalization and participating in the China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction. Data collected included patients’ baseline characteristics; employment status at 12 months after acute myocardial infarction; and, for those who were not employed at 12 months, potential reasons for not returning to work. A logistic regression model was fitted to identify factors associated with returning to work at 12 months. Data were collected from January 1, 2013, through July 17, 2014, and statistical analysis was conducted from August 9, 2016, to August 15, 2018.

Main Outcomes and Measures

Return to work, defined as rejoining the workforce within 12 months after discharge from hospitalization for the index acute myocardial infarction.

Results

Of 1566 patients (130 women and 1436 men; mean [SD] age, 52.2 [9.7] years), 875 patients (55.9%; 95% CI, 53.4%-58.3%) returned to work by 12 months after acute myocardial infarction. Among the 691 patients who did not return to work, 287 (41.5%) were unable to work and/or preferred not to work because of acute myocardial infarction and 131 (19.0%) retired early owing to the acute myocardial infarction. Female sex (relative risk, 0.65; 95% CI, 0.41-0.88), a history of smoking (relative risk, 0.82; 95% CI, 0.65-0.98), and in-hospital complications during the index acute myocardial infarction (relative risk, 0.96; 95% CI, 0.93-0.99) were associated with a lower likelihood of returning to work.

Conclusions and Relevance

Almost half of the previously employed Chinese patients did not return to work within 12 months after acute myocardial infarction. Female sex, history of smoking, and in-hospital complications were associated with a lower likelihood of returning to work.

Trial Registration

ClinicalTrials.gov Identifier: NCT01624909

This cohort study determines the rate of return to work among Chinese patients within 12 months after acute myocardial infarction, classifies the reasons why patients did not return to work, and identifies patient factors associated with returning to work after acute myocardial infarction.

Key Points

Question

What patient factors are associated with return to work within 12 months after myocardial infarction in China?

Findings

In this cohort study of data from the China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction conducted in 53 hospitals across 21 provinces in China, of 1566 patients who were employed at the time of the index hospitalization, only 55.9% returned to work by 12 months after acute myocardial infarction. Women were less likely to return to work, and smoking status and in-hospital complications were the only preventable factors that were associated with a lower likelihood of returning to work.

Meaning

Reducing in-hospital complications and promoting smoking cessation may be important targets for interventions focused on a timely return to the workforce after acute myocardial infarction.

Introduction

Return to work after acute myocardial infarction (AMI) is an important indicator of recovery. It signals a transition from illness to an active social position and has been associated with physical and psychological well-being,^1,2 life satisfaction,³ and quality of life.⁴ Failure to return to work may increase the incidence of depression,^5,6,7 decrease quality of life,⁷ increase the financial burden on patients and their families,⁸ and impose societal costs, such as worsening labor shortages.⁹ Return to work after AMI is particularly important in China, where patients presenting with AMI are younger than in many other countries.¹⁰ Moreover, because of the impending increase in the retirement age to 65 years for many jobs in China, return to work will become a relevant measure of recovery for even more people.

Return to work after AMI involves a combination of physical and psychological functions (able to return), sociodemographic factors (must return), and affinity for work (want to return). Previous studies have shown that returning to work is directly influenced by the recurrence of coronary heart disease,¹¹ psychological function,^1,11,12 and socioeconomic factors.^13,14,15 However, most of these studies were cross-sectional or retrospective, based on relatively small and single-center study samples, and conducted more than a decade ago. To date, to our knowledge, no specific study about returning to work after AMI has been conducted in China, and the proportion of the Chinese population with AMI who return to work and the factors associated with this decision remain largely unknown. It is also unclear whether patients’ reported reasons for not returning to work are associated with their physical health, mental health, or sociodemographic characteristics.

Accordingly, we used data from the China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction (China PEACE Prospective Study of AMI)—one of the largest and most contemporary samples of working-age patients hospitalized for AMI for a study conducted in 53 hospitals across 21 provinces in Chine¹⁶—to determine the rate of return to work within 12 months after AMI, classify the reasons why patients did not return to work, and identify patient factors associated with returning to work. We hypothesized that return to work would be associated with patient sociodemographic and medical characteristics. Our goal was to generate evidence that supports improvements in clinical practice and outcomes, including higher rates of returning to work after AMI in China.

Methods

Study Sample and Data Collection

The China PEACE Prospective Study of AMI consecutively enrolled 5901 patients with AMI aged 18 years or older who were discharged alive from acute care hospitals in China from January 1, 2013, through July 17, 2014. Patient information was collected during the index hospitalization for AMI and after discharge at 1, 6, and 12 months.¹⁶ Medical record data were centrally abstracted for the index hospitalization, and interview data were collected at baseline (ie, index hospitalization) and during follow-up at 1, 6, and 12 months after discharge. Real Data Medical Research Inc, Ningbo, China, abstracted all medical records. All follow-up interviews were conducted either in person or via telephone. After discharge, patients were instructed to return to the hospital for follow-up interviews with site investigators. Telephone interviews were conducted only when in-person interviews were not feasible. Patients were classified as nonresponders after 5 telephone interview attempts with no response. The overall response rate was 97.8% (4118 of 4212). The study was approved by the ethics committee of Fuwai Hospital, the national coordinating center for China PEACE, and, where required, by the local ethics committees of individual hospitals. Patients provided written informed consent. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

For the current study, we restricted the sample to 1662 patients who reported having a job (part-time or full-time) at the time of the index AMI hospitalization, agreed to participate in the follow-up interviews, were discharged alive and not transferred to another acute care hospital, and completed the 12-month interview. Because patients who did not return to work after the index AMI may have retired, we excluded 96 employed patients who had reached retirement age (for most occupations, ≥55 years for women and ≥60 years for men) by the 12-month interview. This restriction did not apply to self-employed patients.

Outcome

Our outcome was return to work, defined as full-time or part-time employment at 12 months after discharge from the index hospitalization for AMI. Among patients who did not return to work within 12 months, we assessed the following reasons for not returning: (1) not returning to work owing to AMI (if a patient reported being unable to work or preferring not to work because of AMI), (2) early retirement owing to AMI (if a patient reported retiring after the index AMI but had not yet reached retirement age), (3) full-time homemaker or unemployed (if a patient reported becoming a full-time homemaker or being laid off after the index AMI), and (4) unspecified reason for not returning to work (if a patient did not specify a reason for leaving the workforce).

Patient and Hospital Characteristics

Patient characteristics included baseline demographic characteristics (age, sex, and marital status), socioeconomic status (income and educational level), cardiovascular risk factors (smoking, hypertension, type 2 diabetes, dyslipidemia, and family history of coronary heart disease), history of cardiovascular disease (angina, coronary heart disease, atrial fibrillation, heart failure, history of AMI, history of percutaneous coronary intervention, and history of coronary artery bypass grafting), in-hospital diagnoses (ST-segment elevation or depression, inferior or anterior AMI, Killip class, and left ventricular ejection fraction), in-hospital revascularization procedures (coronary artery bypass grafting or percutaneous coronary intervention), in-hospital complications (recurrent angina, recurrent AMI, atrial fibrillation, cardiopulmonary resuscitation, ventricular tachycardia, ventricular fibrillation, heart failure, infection, stroke, and bleeding), and length of the index hospital stay. Hospital characteristics included hospital location (urban vs rural), type of hospital (tertiary vs others), teaching status (teaching vs nonteaching), coronary artery bypass grafting capacity (yes or no), and percutaneous coronary intervention capacity (yes or no).

Statistical Analysis

Statistical analysis was conducted from August 9, 2016, to August 15, 2018. We compared patient characteristics between those who returned to work within 12 months after AMI and those who did not return to work using the Mantel-Haenszel test for ordinal variables, χ² test for categorical variables, and Kruskal-Wallis test for continuous variables. We fitted a logistic regression model with the least absolute shrinkage and selection operator method, a shrinkage and variable selection approach for linear regression,^17,18 to identify patient characteristics associated with return to work at 12 months. To obtain a 95% CI of the coefficient for each selected variable, we conducted a nonparametric bootstrap analysis with 1000 iterations and with replacement.^19,20 We also fitted a linear multinomial logistic regression model to evaluate the associations between patient characteristics and each of the 4 reasons for not returning to work, with return to work as the reference. To facilitate interpretation of the results, odds ratios of the selected variables were converted to relative risks (RRs) using the method of Zhang and Yu.²¹ All statistical tests were performed using a 2-sided α value of .05. Analyses were conducted using SAS, version 9.4 (SAS Institute Inc). The study followed the guidelines for developing and evaluating a prediction model, described in the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement.²² Each of the 22 items of the TRIPOD statement was addressed.

Results

Baseline Patient Characteristics

The final study sample included 1566 patients who were in the workforce before the index hospitalization for AMI and were discharged alive across 53 hospitals (Figure 1). The mean (SD) age of these patients was 52.2 (9.7) years; 169 (10.8%) were aged 65 years or older (Table 1). Among the 1566 patients, 130 (8.3%) were women, 267 (17.0%) had a bachelor’s degree or higher, 550 (35.1%) were agricultural workers, and 1462 (93.4%) were married. The 5 most prevalent comorbidities in the population were hypertension (727 [46.4%]), history of coronary heart disease (620 [39.6%]), dyslipidemia (492 [31.4%]), heart failure (345 [22.0%]), and type 2 diabetes (292 [18.6%]). Most patients (1165 [74.4%]) underwent percutaneous coronary intervention during the hospitalization. The median length of stay was 11.0 days (interquartile range, 8.0-14.0 days). There were no substantial differences in patient baseline characteristics between patients who had a job and those who did not have a job at the time of hospitalization for the index AMI (eTable 1 in the Supplement).

Figure 1. — AMI indicates acute myocardial infarction; China PEACE Prospective Study of AMI, China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction.

Table 1. Comparison of Baseline Characteristics Between Patients Who Did and Patients Who Did Not Return to Work Within 12 Months After Acute Myocardial Infarction.

Characteristic	Patients, No. (%)			P Value
Characteristic	Total (N = 1566)	Did Not Return to Work (n = 691)	Returned to Work (n = 875)
Sociodemographic characteristics
Age, mean (SD), y	52.2 (9.7)	54.5 (10.1)	50.3 (9.0)	<.001
Female	130 (8.3)	86 (12.4)	44 (5.0)	<.001
Married	1462 (93.4)	642 (92.9)	820 (93.7)	.53
College education	267 (17.0)	90 (13.0)	177 (20.2)	<.001
Occupation
Worker	395 (25.2)	162 (23.4)	233 (26.6)	<.001
Farmer	550 (35.1)	292 (42.3)	258 (29.5)
Self-employed	108 (6.9)	43 (6.2)	65 (7.4)
Other	513 (32.8)	194 (28.1)	319 (36.5)
Income last year, RMB (US $)
<30 000 (<4400)	524 (33.5)	249 (36.0)	275 (31.4)	<.001
30 000-70 000 (4400-10 250)	451 (28.8)	182 (26.3)	269 (30.7)
>70 000 (>10 250)	228 (14.6)	71 (10.3)	157 (17.9)
Unreported	363 (23.2)	189 (27.4)	174 (19.9)
Cardiovascular risk factors
Prior smoking	196 (12.5)	99 (14.3)	97 (11.1)	.05
Hypertension	727 (46.4)	342 (49.5)	385 (44.0)	.03
Type 2 diabetes	292 (18.6)	120 (17.4)	172 (19.7)	.25
Dyslipidemia	492 (31.4)	222 (32.1)	270 (30.9)	.59
Family history of coronary heart disease	187 (11.9)	81 (11.7)	106 (12.1)	.81
Disease history
Angina	48 (3.1)	25 (3.6)	23 (2.6)	.26
Acute myocardial infarction	80 (5.1)	32 (4.6)	48 (5.5)	.45
Percutaneous coronary intervention	82 (5.2)	35 (5.1)	47 (5.4)	.79
Coronary artery bypass grafting	1 (0.1)	0	1 (0.1)	.37
Coronary heart disease	620 (39.6)	275 (39.8)	345 (39.4)	.88
Ventricular tachycardia or fibrillation	38 (2.4)	17 (2.5)	21 (2.4)	.94
Atrial fibrillation	32 (2.0)	21 (3.0)	11 (1.3)	.01
Heart failure	345 (22.0)	161 (23.3)	184 (21.0)	.28
Valvular heart disease	1 (0.1)	1 (0.1)	0	.26
Peripheral vascular disease	7 (0.4)	3 (0.4)	4 (0.5)	.95
Ischemic stroke	4 (0.3)	3 (0.4)	1 (0.1)	.21
Chronic renal failure	6 (0.4)	3 (0.4)	3 (0.3)	.77
Clinical characteristics
Non–ST-segment elevation acute myocardial infarction	103 (6.6)	45 (6.5)	58 (6.6)	.93
Killip class 3-4	63 (4.0)	30 (4.3)	33 (3.8)	.57
Inferior wall acute myocardial infarction	627 (40.0)	283 (41.0)	344 (39.3)	.51
Anterior wall acute myocardial infarction	315 (20.1)	121 (17.5)	194 (22.2)	.02
Ischemia >20 min	1166 (74.5)	515 (74.5)	651 (74.4)	.95
Ejection fraction <40%	84 (5.4)	45 (6.5)	39 (4.5)	.07
Coronary artery bypass grafting during index hospitalization	49 (3.1)	27 (3.9)	22 (2.5)	.12
Percutaneous coronary intervention during index hospitalization	1165 (74.4)	523 (75.7)	642 (73.4)	.30
Length of stay, median (IQR), d	11.0 (8.0-14.0)	11.0 (8.0-14.0)	11.0 (8.0-14.0)	.48
In-hospital complications
Recurrent angina	368 (23.5)	181 (26.2)	187 (21.4)	.03
Recurrent acute myocardial infarction	16 (1.0)	9 (1.3)	7 (0.8)	.33
Atrial fibrillation	27 (1.7)	17 (2.5)	10 (1.1)	.047
Cardiopulmonary resuscitation	17 (1.1)	7 (1.0)	10 (1.1)	.81
Ventricular tachycardia	81 (5.2)	42 (6.1)	39 (4.5)	.15
Ventricular fibrillation	40 (2.6)	14 (2.0)	26 (3.0)	.24
New-onset heart failure	95 (6.1)	47 (6.8)	48 (5.5)	.28
Infection	190 (12.1)	95 (13.7)	95 (10.9)	.08
Stroke	23 (1.5)	16 (2.3)	7 (0.8)	.01
Bleeding	136 (8.7)	67 (9.7)	69 (7.9)	.21
Region
Central	757 (48.3)	357 (51.7)	400 (45.7)	.02
East	619 (39.5)	265 (38.4)	354 (40.5)
West	190 (12.1)	69 (10.0)	121 (13.8)
Urban	1244 (79.4)	555 (80.3)	689 (78.7)	.44
Hospital type
Teaching hospital	1171 (74.8)	507 (73.4)	664 (75.9)	.26
Tertiary hospital	1285 (82.1)	580 (83.9)	705 (80.6)	.09

Open in a new tab

Abbbreviations: IQR, interquartile range; RMB, renminbi.

Returning to Work

In total, 875 patients (55.9%; 95% CI, 53.4%-58.3%) had returned to work within 12 months after the index hospitalization for AMI (Figure 1). Among the 691 patients who did not return, 287 (41.5%) were unable to work and/or preferred not to work because of AMI, 131 (19.0%) retired early because of AMI, 44 (6.4%) became full-time homemakers or were unemployed, and 229 (33.1%) did not specify a reason for not returning to work. We observed differences in baseline patient characteristics by return to work status (Table 1) and reason for not returning to work (Table 2). Compared with patients who returned to work within 12 months, those who did not return were older and more likely to be female, be agricultural workers at the time of the index AMI, have hypertension, and have major adverse events (stroke, atrial fibrillation, and angina) during the index hospital stay. No significant differences were observed in family history of coronary heart disease or length of hospital stay (Table 1). Among patients who did not return to work, the recurrence of angina was the only clinical factor that differed significantly by reason for not returning; there were also differences in sociodemographic factors including age, educational level, income, and occupation (Table 2).

Table 2. Baseline Patient Characteristics by Reason for Not Returning to Work.

Characteristic	Patients, No. (%)				P Value
Characteristic	AMI-Related (n = 287)	AMI-Related Early Retirement (n = 131)	Full-time Homemaker or Unemployed (n = 44)	Unspecified (n = 229)	P Value
Sociodemographic characteristics
Age, mean (SD), y	56.1 (9.5)	53.9 (8.4)	56.2 (10.2)	52.6 (11.2)	<.001
Female	38 (13.2)	6 (4.6)	13 (29.5)	29 (12.7)	<.001
Married	265 (92.3)	124 (94.7)	40 (90.9)	213 (93.0)	.80
College education	14 (4.9)	29 (22.1)	3 (6.8)	44 (19.2)	<.001
Occupation
Worker	68 (23.7)	42 (32.1)	6 (13.6)	46 (20.1)	<.001
Farmer	149 (51.9)	26 (19.8)	26 (59.1)	91 (39.7)
Self-employed	18 (6.3)	5 (3.8)	4 (9.1)	16 (7.0)
Other	52 (18.1)	58 (44.3)	8 (18.2)	76 (33.2)
Income last year, RMB (US $)
<30 000 (<4400)	133 (46.3)	22 (16.8)	21 (47.7)	73 (31.9)	<.001
30 000-70 000 (4400-10 250)	70 (24.4)	48 (36.6)	11 (25.0)	53 (23.1)
>70 000 (>10 250)	17 (5.9)	24 (18.3)	2 (4.5)	28 (12.2)
Unreported	67 (23.3)	37 (28.2)	10 (22.7)	75 (32.8)
Cardiovascular risk factors
Prior smoking	48 (16.7)	16 (12.2)	8 (18.2)	27 (11.8)	.31
Family history of coronary heart disease	30 (10.5)	18 (13.7)	7 (15.9)	26 (11.4)	.63
Hypertension	145 (50.5)	62 (47.3)	20 (45.5)	115 (50.2)	.87
Type 2 diabetes	47 (16.4)	32 (24.4)	8 (18.2)	33 (14.4)	.10
Dyslipidemia	94 (32.8)	52 (39.7)	15 (34.1)	61 (26.6)	.08
Disease history
Angina	13 (4.5)	6 (4.6)	1 (2.3)	5 (2.2)	.46
AMI	15 (5.2)	8 (6.1)	0	9 (3.9)	.35
Percutaneous coronary intervention	13 (4.5)	11 (8.4)	0	11 (4.8)	.13
Coronary artery bypass grafting	0	0	0	0	NA
Coronary heart disease	126 (43.9)	56 (42.7)	14 (31.8)	79 (34.5)	.10
Ventricular tachycardia or fibrillation	8 (2.8)	1 (0.8)	2 (4.5)	6 (2.6)	.47
Atrial fibrillation	10 (3.5)	3 (2.3)	1 (2.3)	7 (3.1)	.91
Heart failure	66 (23.0)	37 (28.2)	8 (18.2)	50 (21.8)	.44
Valvular heart disease	0	1 (0.8)	0	0	.23
Peripheral vascular disease	0	1 (0.8)	0	2 (0.9)	.43
Ischemic stroke	1 (0.3)	1 (0.8)	1 (2.3)	0	.19
Chronic renal failure	1 (0.3)	0	0	2 (0.9)	.61
Clinical characteristics
Non–ST-segment elevation AMI	19 (6.6)	6 (4.6)	1 (2.3)	19 (8.3)	.35
Killip class 3-4	11 (3.8)	11 (8.4)	2 (4.5)	6 (2.6)	.07
Inferior wall AMI	124 (43.2)	54 (41.2)	19 (43.2)	86 (37.6)	.62
Anterior wall AMI	51 (17.8)	22 (16.8)	12 (27.3)	36 (15.7)	.33
Heart failure on admission	66 (23.0)	37 (28.2)	8 (18.2)	50 (21.8)	.44
Ischemia >20 min	228 (79.4)	96 (73.3)	29 (65.9)	162 (70.7)	.07
Ejection fraction <40%	17 (5.9)	9 (6.9)	2 (4.5)	17 (7.4)	.85
Coronary artery bypass grafting during index hospitalization	11 (3.8)	5 (3.8)	1 (2.3)	10 (4.4)	.93
Percutaneous coronary intervention during index hospitalization	208 (72.5)	106 (80.9)	32 (72.7)	177 (77.3)	.25
Length of stay, median (IQR), d	10.0 (8.0-14.0)	12.0 (8.0-16.0)	10.5 (7.0-15.5)	10.0 (7.0-14.0)	.04
In-hospital complications
Recurrent angina	92 (32.1)	36 (27.5)	10 (22.7)	43 (18.8)	.008
Recurrent AMI	6 (2.1)	2 (1.5)	1 (2.3)	0	.19
Atrial fibrillation	10 (3.5)	3 (2.3)	1 (2.3)	3 (1.3)	.47
Cardiopulmonary resuscitation	4 (1.4)	1 (0.8)	0	2 (0.9)	.80
Ventricular tachycardia	22 (7.7)	10 (7.6)	2 (4.5)	8 (3.5)	.20
Ventricular fibrillation	5 (1.7)	2 (1.5)	0	7 (3.1)	.49
New-onset heart failure	14 (4.9)	14 (10.7)	2 (4.5)	17 (7.4)	.15
Infection	42 (14.6)	26 (19.8)	6 (13.6)	21 (9.2)	.04
Stroke	11 (3.8)	1 (0.8)	0	4 (1.7)	.13
Bleeding	26 (9.1)	18 (13.7)	5 (11.4)	18 (7.9)	.31
Region
Central	144 (50.2)	71 (54.2)	22 (50.0)	120 (52.4)	.78
East	112 (39.0)	44 (33.6)	18 (40.9)	91 (39.7)
West	31 (10.8)	16 (12.2)	4 (9.1)	18 (7.9)
Urban	203 (70.3)	126 (96.2)	34 (77.3)	192 (83.8)	<.001
Hospital type
Teaching hospital	193 (67.3)	97 (74.1)	33 (75.0)	184 (80.4)	.01
Tertiary hospital	219 (76.3)	125 (95.4)	34 (77.3)	202 (88.2)	<.001

Open in a new tab

Abbreviations: AMI, acute myocardial infarction; IQR, interquartile range; NA, not applicable; RMB, renminbi.

Factors Associated with Returning to Work

The least absolute shrinkage and selection operator method selected 13 candidate factors that had nonzero coefficients after shrinkage (eTable 2 in the Supplement). The bootstrap simulation removed 6 of these factors with a 95% CI containing zero. The remaining 7 factors included patient demographics (female sex and college degree), comorbidities (type 2 diabetes and dyslipidemia), hospital diagnoses and tests (anterior wall AMI), and in-hospital complications (Figure 2). Factors associated with being more likely to return to work included having a college education (RR, 1.30; 95% CI, 1.02-1.56), history of type 2 diabetes (RR, 1.24; 95% CI, 1.02-1.44), and AMI of the anterior wall (RR, 1.22; 95% CI, 1.01-1.41). Factors associated with a lower likelihood of returning to work included female sex (RR, 0.65; 95% CI, 0.41-0.88), history of smoking (RR, 0.82; 95% CI, 0.65-0.98), history of dyslipidemia (RR, 0.89; 95% CI, 0.77-0.995), and in-hospital complications during the index AMI (RR, 0.96; 95% CI, 0.93-0.99).

Figure 2. — The patient characteristics associated with return to work at 12 months are shown in the first column.

The multinomial logistic regression with the least absolute shrinkage and selection operator method and bootstrap analysis identified 15 variables that were statistically significantly associated with at least 1 of the 4 “no return to work” categories relative to the “return to work” category (eFigure in the Supplement). For example, patients who developed adverse events during hospitalization for the index AMI and elderly patients were more likely to not return to work owing to AMI, and female patients were more likely to become full-time homemakers or unemployed after AMI.

Discussion

In this Chinese national cohort, approximately half of the previously employed individuals returned to work in the year after hospitalization for AMI. With an estimated 2.5 million people in China with a history of AMI,²³ workforce losses of this magnitude impose a substantial personal and societal burden. Our study identified a diverse array of demographic, socioeconomic, and clinical factors that were associated with return to work and might be amenable to interventions that aim to improve recovery after AMI.

The findings from the China PEACE Prospective Study of AMI extend the prior literature in several ways. Our study provides the most contemporary, nationwide prospective evaluation of the rate of returning to work after AMI in China, as well as the factors associated with returning to work after AMI. Less than 60% of patients in our study returned to work within 12 months after discharge for AMI. This rate is relatively low when compared with data from other countries in which rates have ranged from 74% to 86% during the past 2 decades.^{1,4,8,11,24,25} Several factors may explain this observation. First, the availability of cardiac rehabilitation in China is low, and the quality of rehabilitation services is generally poor.²⁶ Cardiac rehabilitation significantly reduces long-term cardiovascular mortality, increases functional capacity, improves levels of pertinent risk factors, and contributes to overall improvement in psychological status and well-being^27,28; it is also positively associated with a timely return to work.¹³ Second, China has an age-based retirement policy, which currently forces retirement at age 60 years for men and 55 years for women.²⁹ Because the mean age of our study population was 52.2 years, enforcement of the retirement policy may have negatively influenced patients’ motivation to return to work, particularly for women who not only have a retirement age 5 years younger than men but also have an older age at onset of AMI compared with men (72.0 vs 65.6 years, respectively).³⁰ Long working hours and lack of overtime pay may also have been barriers to returning to work. In 2011, China ranked fourth in the world in terms of hours spent at work,³¹ and overtime is rarely compensated.^32,33 Last, previous studies have shown that the rate of return to work after AMI varies within and across countries,⁸ with rates of 76% to 86% in the United States,^4,24 80% in the United Kingdom,¹¹ 76% in the northern Netherlands,³⁴ 77% in Iran,²⁵ 62% in Germany,¹⁴ and 74.0% in Finland.⁸ This variation may reflect differences in sampling methods, current unemployment rates, sickness benefits, insurance support for workers, social welfare systems, or employment protection laws across countries.

We identified several sociodemographic and clinical characteristics that were associated with failure to return to work. Contrary to several reports, women in our study were less likely than men to return to work after AMI.^1,8,11,25 This difference for women could reflect poorer health status, more depression, or less social support after AMI compared with men.^35,36,37 Even if they did return to work after AMI, more women quit their jobs after returning to work compared with men.³⁸ In addition, employed women have less job security, less job control, poorer contractual working conditions, and poorer self-perceived physical and mental health than men, which may negatively affect their decision to return to work.³⁹ We also demonstrated that major in-hospital complications were associated with a reduced likehood of returning to work. Although some of these common complications may reflect the inherent nature of the disease,⁴⁰ others are potentially preventable.⁴¹ The incidence of in-hospital complications has been suggested as a proxy for the quality of hospital care.⁴² Our results suggest that preventing complications during hospitalization might improve overall care and promote return to work after AMI.

More important, we reported the reason for not returning to work from the patients’ perspective. Previous studies showed that patients’ perceptions of illness affected their decisions to return to work after AMI.^14,43 However, comparison of patients who did not attribute their failure to return to work to the AMI with those who did not return to work because of the AMI revealed no significant differences in cardiovascular risk factors, disease history, or clinical characteristics. Such findings indicate that sociodemographic characteristics, such as age, educational level, occupation, and income, may be more important factors in the decision to return to work.

Implications

From a societal perspective, our study is of particular importance for China. Our findings signal the need for interventions that promote a timely return to work after AMI in China to mitigate a preventable decline in the working-age population. Labor-intensive industries are still a vital component of China’s economy, and economic growth has relied, at least in part, on the country’s high ratio of working-age to non–working-age individuals. However, China’s working-age population declined from 2013 to 2015,⁴⁴ and the morbidity burden of AMI continues to rise.²³ The World Bank estimates that the number of people with AMI in China will increase from 2.5 million to 23 million by 2030.⁴⁵ Promoting a return to work after AMI in China may slow the decline in the workforce. The Chinese government’s current consideration of older retirement age may further increase the need to manage this important issue. Our study confirms that factors associated with returning to work after AMI in Western societies are also essential determinants in China (eg, history of smoking).^7,46 Diabetes and prior dyslipidemia may also be associated with the return to work after AMI, although this finding is contrary to a previous study.²⁴ In conclusion, we identified 2 clear targets for intervention after AMI: reducing in-hospital complications and promoting smoking cessation.

Limitations

Certain limitations should be considered when interpreting our results. Only patients who completed the interview at 12 months were included, possibly introducing selection bias. Only 8.3% of our total study population were women. This low proportion likely reflects a combination of the relatively young age of retirement for women in China (55 years) and the older age at onset of first AMI in women compared with men.⁷ Women may have already retired before experiencing their first AMI. There were more unemployed women in the baseline than employed (324 of 958 [33.8%] vs 130 of 1566 [8.3%], respectively; eTable 1 in the Supplement). Nevertheless, the lack of women may limit the generalizability of the study. We fit fixed-effects models to conduct the analysis. Patients, however, may be clustered within hospitals and regions. We did not have data for the specific date of each patient’s return to work after AMI and the duration that the patient remained at the job. It is possible that patients who returned to work after AMI later withdrew from the workforce before our 12-month assessment. These patients were counted as having not returned to work, and they may have had a better recovery than those who never returned to work at all. We also had no information on other events after hospitalization, such as recurrent AMI, rehospitalization, and bleeding, which may influence the return to work. Although 229 of the 691 patients (33.1%) in our study who failed to return to work declared that they left the workforce for reasons unrelated to AMI, we did not have detailed explanations for these decisions. Such information would be helpful in guiding patient-centered interventions, and close attention to patient decision making is warranted in future studies. We did not collect information on the working environment or patient-reported quality of work factors such as job satisfaction, motivation to resume work, workplace stress, and job security. These factors may influence a person’s decision to reenter the labor force beyond health and socioeconomic considerations.

Conclusions

Among employed patients hospitalized with AMI in China, nearly half did not return to work within 12 months. Women, prior smokers, and those who experienced adverse in-hospital events were less likely to return to work after AMI. Reducing in-hospital complications, in particular, may be an important target for interventions focused on the timely return to the workforce after AMI.

Supplement.

eTable 1. Comparison of Baseline Characteristics by Employment Status at Baseline Among Patients Who Were Discharged Alive, Did Not Transfer to Another Acute-Care Hospital, Agreed to Participate in the Follow-up Surveys, Completed the 12-Month Interview, and Did Not Reach Retirement Age

eTable 2. Factors Selected by a Logistic Model With the LASSO Method

eFigure. Variables Statistically Significantly Associated With at Least 1 of the 4 “No Return to Work” Categories

Click here for additional data file.^{(540.8KB, pdf)}

References

1.Brink E, Brändström Y, Cliffordsson C, Herlitz J, Karlson BW. Illness consequences after myocardial infarction: problems with physical functioning and return to work. J Adv Nurs. 2008;64(6):-. doi: 10.1111/j.1365-2648.2008.04820.x [DOI] [PubMed] [Google Scholar]
2.Rost K, Smith GR. Return to work after an initial myocardial infarction and subsequent emotional distress. Arch Intern Med. 1992;152(2):381-385. doi: 10.1001/archinte.1992.00400140121026 [DOI] [PubMed] [Google Scholar]
3.Vestling M, Tufvesson B, Iwarsson S. Indicators for return to work after stroke and the importance of work for subjective well-being and life satisfaction. J Rehabil Med. 2003;35(3):127-131. doi: 10.1080/16501970310010475 [DOI] [PubMed] [Google Scholar]
4.McBurney CR, Eagle KA, Kline-Rogers EM, Cooper JV, Smith DE, Erickson SR. Work-related outcomes after a myocardial infarction. Pharmacotherapy. 2004;24(11):1515-1523. doi: 10.1592/phco.24.16.1515.50946 [DOI] [PubMed] [Google Scholar]
5.Mossakowski KN. The influence of past unemployment duration on symptoms of depression among young women and men in the United States. Am J Public Health. 2009;99(10):1826-1832. doi: 10.2105/AJPH.2008.152561 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Dooley D, Fielding J, Levi L. Health and unemployment. Annu Rev Public Health. 1996;17:449-465. doi: 10.1146/annurev.pu.17.050196.002313 [DOI] [PubMed] [Google Scholar]
7.Warraich HJ, Kaltenbach LA, Fonarow GC, Peterson ED, Wang TY. Adverse change in employment status after acute myocardial infarction: analysis from the TRANSLATE-ACS study. Circ Cardiovasc Qual Outcomes. 2018;11(6):e004528. doi: 10.1161/CIRCOUTCOMES.117.004528 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Hämäläinen H, Mäki J, Virta L, et al. . Return to work after first myocardial infarction in 1991-1996 in Finland. Eur J Public Health. 2004;14(4):350-353. doi: 10.1093/eurpub/14.4.350 [DOI] [PubMed] [Google Scholar]
9.Ilmarinen J. The ageing workforce—challenges for occupational health. Occup Med (Lond). 2006;56(6):362-364. doi: 10.1093/occmed/kql046 [DOI] [PubMed] [Google Scholar]
10.Li J, Li X, Wang Q, et al. ; China PEACE Collaborative Group . ST-segment elevation myocardial infarction in China from 2001 to 2011 (the China PEACE-Retrospective Acute Myocardial Infarction Study): a retrospective analysis of hospital data [retracted in: Lancet. 2015;385(9966):402]. Lancet. 2015;385(9966):441-451. doi: 10.1016/S0140-6736(14)60921-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Bhattacharyya MR, Perkins-Porras L, Whitehead DL, Steptoe A. Psychological and clinical predictors of return to work after acute coronary syndrome. Eur Heart J. 2007;28(2):160-165. doi: 10.1093/eurheartj/ehl440 [DOI] [PubMed] [Google Scholar]
12.O’Neil A, Sanderson K, Oldenburg B. Depression as a predictor of work resumption following myocardial infarction (MI): a review of recent research evidence. Health Qual Life Outcomes. 2010;8:95. doi: 10.1186/1477-7525-8-95 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Boudrez H, De Backer G, Comhaire B. Return to work after myocardial infarction: results of a longitudinal population based study. Eur Heart J. 1994;15(1):32-36. doi: 10.1093/oxfordjournals.eurheartj.a060376 [DOI] [PubMed] [Google Scholar]
14.Mittag O, Kolenda KD, Nordman KJ, Bernien J, Maurischat C. Return to work after myocardial infarction/coronary artery bypass grafting: patients’ and physicians’ initial viewpoints and outcome 12 months later. Soc Sci Med. 2001;52(9):1441-1450. doi: 10.1016/S0277-9536(00)00250-1 [DOI] [PubMed] [Google Scholar]
15.Farkas J, Cerne K, Lainscak M, Keber I. Return to work after acute myocardial infarction—listen to your doctor! Int J Cardiol. 2008;130(1):e14-e16. doi: 10.1016/j.ijcard.2007.07.041 [DOI] [PubMed] [Google Scholar]
16.Li J, Dreyer RP, Li X, et al. ; China PEACE Collaborative Group . China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction: study design. Chin Med J (Engl). 2016;129(1):72-80. doi: 10.4103/0366-6999.172596 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc B. 1996;58(1):267-288. [Google Scholar]
18.Santosa F, Symes WW. Linear inversion of band-limited reflection seismograms. SIAM J Sci Statist Comput. 1986;7(4):1307-1330. doi: 10.1137/0907087 [DOI] [Google Scholar]
19.Bach FR. Bolasso: model consistent Lasso estimation through the bootstrap. Paper presented at: Proceedings of the 25th International Conference on Machine Learning; July 5-9, 2008; Helsinki, Finland. [Google Scholar]
20.Laurin C, Boomsma D, Lubke G. The use of vector bootstrapping to improve variable selection precision in Lasso models. Stat Appl Genet Mol Biol. 2016;15(4):305-320. doi: 10.1515/sagmb-2015-0043 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Zhang J, Yu KF. What’s the relative risk? a method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998;280(19):1690-1691. doi: 10.1001/jama.280.19.1690 [DOI] [PubMed] [Google Scholar]
22.Moons KG, Altman DG, Reitsma JB, et al. . Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1-W73. doi: 10.7326/M14-0698 [DOI] [PubMed] [Google Scholar]
23.National Center for Cardiovascular Diseases Report on cardiovascular diseases in China 2014. Chin Circ J. 2015;(7):617-622. [Google Scholar]
24.Dreyer RP, Xu X, Zhang W, et al. . Return to work after acute myocardial infarction: comparison between young women and men. Circ Cardiovasc Qual Outcomes. 2016;9(2)(suppl 1):S45-S52. doi: 10.1161/CIRCOUTCOMES.115.002611 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Mirmohammadi SJ, Sadr-Bafghi SM, Mehrparvar AH, et al. . Evaluation of the return to work and its duration after myocardial infarction. ARYA Atheroscler. 2014;10(3):137-140. [PMC free article] [PubMed] [Google Scholar]
26.Thompson DR, Yu C-M. Cardiac rehabilitation: China In: Perk J, Mathes P, Gohlke H, et al. , eds. Cardiovascular Prevention and Rehabilitation. London, UK: Springer; 2007:48-51. doi: 10.1007/978-1-84628-502-8_10 [DOI] [Google Scholar]
27.Oldridge NB, Guyatt GH, Fischer ME, Rimm AA. Cardiac rehabilitation after myocardial infarction: combined experience of randomized clinical trials. JAMA. 1988;260(7):945-950. doi: 10.1001/jama.1988.03410070073031 [DOI] [PubMed] [Google Scholar]
28.Bittner V, Oberman A. Efficacy studies in coronary rehabilitation. Cardiol Clin. 1993;11(2):333-347. doi: 10.1016/S0733-8651(18)30183-8 [DOI] [PubMed] [Google Scholar]
29.Manion M. Retirement of Revolutionaries in China: Public Policies, Social Norms, Private Interests. Princeton, NJ: Princeton University Press; 2014. [Google Scholar]
30.Benjamin EJ, Virani SS, Callaway CW, et al. ; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee . Heart disease and stroke statistics—2018 update: a report from the American Heart Association [published correction appears in Circulation. 2018;137(12):e493]. Circulation. 2018;137(12):e67-e492. doi: 10.1161/CIR.0000000000000558 [DOI] [PubMed] [Google Scholar]
31.Mishra V, Smyth R. Working hours in Chinese enterprises: evidence from matched employer–employee data. Ind Relat J. 2013;44(1):57-77. doi: 10.1111/j.1468-2338.2012.00702.x [DOI] [Google Scholar]
32.Messenger JC, Lee S, McCann D. Working Time Around the World: Trends in Working Hours, Laws, and Policies in a Global Comparative Perspective. New York, NY: Taylor & Francis; 2007. [Google Scholar]
33.Zeng X, Lu L, Idris SU. . Working Time in Transition: The Dual Task of Standardization and Flexibilization in China, Conditions of Work and Employment Series No. 11. Geneva, Switzerland: International Labour Office; 2005. [Google Scholar]
34.de Jonge P, Zuidersma M, Bültmann U. The presence of a depressive episode predicts lower return to work rate after myocardial infarction. Gen Hosp Psychiatry. 2014;36(4):363-367. doi: 10.1016/j.genhosppsych.2014.03.006 [DOI] [PubMed] [Google Scholar]
35.Smolderen KG, Strait KM, Dreyer RP, et al. . Depressive symptoms in younger women and men with acute myocardial infarction: insights from the VIRGO study. J Am Heart Assoc. 2015;4(4):e001424. doi: 10.1161/JAHA.114.001424 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Dreyer RP, Wang Y, Strait KM, et al. . Gender differences in the trajectory of recovery in health status among young patients with acute myocardial infarction: results from the Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients (VIRGO) Study. Circulation. 2015;131(22):1971-1980. doi: 10.1161/CIRCULATIONAHA.114.014503 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Kristofferzon ML, Löfmark R, Carlsson M. Myocardial infarction: gender differences in coping and social support. J Adv Nurs. 2003;44(4):360-374. doi: 10.1046/j.0309-2402.2003.02815.x [DOI] [PubMed] [Google Scholar]
38.Smedegaard L, Numé AK, Charlot M, Kragholm K, Gislason G, Hansen PR. Return to work and risk of subsequent detachment from employment after myocardial infarction: insights from Danish nationwide registries. J Am Heart Assoc. 2017;6(10):e006486. doi: 10.1161/JAHA.117.006486 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Campos-Serna J, Ronda-Pérez E, Artazcoz L, Moen BE, Benavides FG. Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review. Int J Equity Health. 2013;12:57. doi: 10.1186/1475-9276-12-57 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Reed GW, Rossi JE, Cannon CP. Acute myocardial infarction. Lancet. 2017;389(10065):197-210. doi: 10.1016/S0140-6736(16)30677-8 [DOI] [PubMed] [Google Scholar]
41.Wang Y, Eldridge N, Metersky ML, et al. . National trends in patient safety for four common conditions, 2005-2011. N Engl J Med. 2014;370(4):341-351. doi: 10.1056/NEJMsa1300991 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Wang Y, Eldridge N, Metersky ML, et al. . Association between hospital performance on patient safety and 30-day mortality and unplanned readmission for Medicare fee-for-service patients with acute myocardial infarction. J Am Heart Assoc. 2016;5(7):e003731. doi: 10.1161/JAHA.116.003731 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Slebus FGJH, Peters RJ, Kuijer PP, Willems JH, Sluiter JK, Frings-Dresen MH. Factors Associated With Return to Work After Admission for Acute Coronary Syndrome: The Patient’s Perspective [dissertation]. Amsterdam, the Netherlands: University of Amsterdam; 2009. [Google Scholar]
44.National Bureau of Statistics of China Statistical Communiqué of the People’s Republic of China on the 2015 National Economic and Social Development. Beijing, China: China Statistics Press; 2016. [Google Scholar]
45.Wang S, Marquez P, Langenbrunner J. Toward a Healthy and Harmonious Life in China: Stemming the Rising Tide of Non-communicable Diseases. Washington, DC: World Bank; 2011. [Google Scholar]
46.Abbas AE, Brodie B, Stone G, et al. . Frequency of returning to work one and six months following percutaneous coronary intervention for acute myocardial infarction. Am J Cardiol. 2004;94(11):1403-1405. doi: 10.1016/j.amjcard.2004.08.014 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable 2. Factors Selected by a Logistic Model With the LASSO Method

eFigure. Variables Statistically Significantly Associated With at Least 1 of the 4 “No Return to Work” Categories

Click here for additional data file.^{(540.8KB, pdf)}

[zoi180210r1] 1.Brink E, Brändström Y, Cliffordsson C, Herlitz J, Karlson BW. Illness consequences after myocardial infarction: problems with physical functioning and return to work. J Adv Nurs. 2008;64(6):-. doi: 10.1111/j.1365-2648.2008.04820.x [DOI] [PubMed] [Google Scholar]

[zoi180210r2] 2.Rost K, Smith GR. Return to work after an initial myocardial infarction and subsequent emotional distress. Arch Intern Med. 1992;152(2):381-385. doi: 10.1001/archinte.1992.00400140121026 [DOI] [PubMed] [Google Scholar]

[zoi180210r3] 3.Vestling M, Tufvesson B, Iwarsson S. Indicators for return to work after stroke and the importance of work for subjective well-being and life satisfaction. J Rehabil Med. 2003;35(3):127-131. doi: 10.1080/16501970310010475 [DOI] [PubMed] [Google Scholar]

[zoi180210r4] 4.McBurney CR, Eagle KA, Kline-Rogers EM, Cooper JV, Smith DE, Erickson SR. Work-related outcomes after a myocardial infarction. Pharmacotherapy. 2004;24(11):1515-1523. doi: 10.1592/phco.24.16.1515.50946 [DOI] [PubMed] [Google Scholar]

[zoi180210r5] 5.Mossakowski KN. The influence of past unemployment duration on symptoms of depression among young women and men in the United States. Am J Public Health. 2009;99(10):1826-1832. doi: 10.2105/AJPH.2008.152561 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r6] 6.Dooley D, Fielding J, Levi L. Health and unemployment. Annu Rev Public Health. 1996;17:449-465. doi: 10.1146/annurev.pu.17.050196.002313 [DOI] [PubMed] [Google Scholar]

[zoi180210r7] 7.Warraich HJ, Kaltenbach LA, Fonarow GC, Peterson ED, Wang TY. Adverse change in employment status after acute myocardial infarction: analysis from the TRANSLATE-ACS study. Circ Cardiovasc Qual Outcomes. 2018;11(6):e004528. doi: 10.1161/CIRCOUTCOMES.117.004528 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r8] 8.Hämäläinen H, Mäki J, Virta L, et al. . Return to work after first myocardial infarction in 1991-1996 in Finland. Eur J Public Health. 2004;14(4):350-353. doi: 10.1093/eurpub/14.4.350 [DOI] [PubMed] [Google Scholar]

[zoi180210r9] 9.Ilmarinen J. The ageing workforce—challenges for occupational health. Occup Med (Lond). 2006;56(6):362-364. doi: 10.1093/occmed/kql046 [DOI] [PubMed] [Google Scholar]

[zoi180210r10] 10.Li J, Li X, Wang Q, et al. ; China PEACE Collaborative Group . ST-segment elevation myocardial infarction in China from 2001 to 2011 (the China PEACE-Retrospective Acute Myocardial Infarction Study): a retrospective analysis of hospital data [retracted in: Lancet. 2015;385(9966):402]. Lancet. 2015;385(9966):441-451. doi: 10.1016/S0140-6736(14)60921-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r11] 11.Bhattacharyya MR, Perkins-Porras L, Whitehead DL, Steptoe A. Psychological and clinical predictors of return to work after acute coronary syndrome. Eur Heart J. 2007;28(2):160-165. doi: 10.1093/eurheartj/ehl440 [DOI] [PubMed] [Google Scholar]

[zoi180210r12] 12.O’Neil A, Sanderson K, Oldenburg B. Depression as a predictor of work resumption following myocardial infarction (MI): a review of recent research evidence. Health Qual Life Outcomes. 2010;8:95. doi: 10.1186/1477-7525-8-95 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r13] 13.Boudrez H, De Backer G, Comhaire B. Return to work after myocardial infarction: results of a longitudinal population based study. Eur Heart J. 1994;15(1):32-36. doi: 10.1093/oxfordjournals.eurheartj.a060376 [DOI] [PubMed] [Google Scholar]

[zoi180210r14] 14.Mittag O, Kolenda KD, Nordman KJ, Bernien J, Maurischat C. Return to work after myocardial infarction/coronary artery bypass grafting: patients’ and physicians’ initial viewpoints and outcome 12 months later. Soc Sci Med. 2001;52(9):1441-1450. doi: 10.1016/S0277-9536(00)00250-1 [DOI] [PubMed] [Google Scholar]

[zoi180210r15] 15.Farkas J, Cerne K, Lainscak M, Keber I. Return to work after acute myocardial infarction—listen to your doctor! Int J Cardiol. 2008;130(1):e14-e16. doi: 10.1016/j.ijcard.2007.07.041 [DOI] [PubMed] [Google Scholar]

[zoi180210r16] 16.Li J, Dreyer RP, Li X, et al. ; China PEACE Collaborative Group . China Patient-centered Evaluative Assessment of Cardiac Events Prospective Study of Acute Myocardial Infarction: study design. Chin Med J (Engl). 2016;129(1):72-80. doi: 10.4103/0366-6999.172596 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r17] 17.Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc B. 1996;58(1):267-288. [Google Scholar]

[zoi180210r18] 18.Santosa F, Symes WW. Linear inversion of band-limited reflection seismograms. SIAM J Sci Statist Comput. 1986;7(4):1307-1330. doi: 10.1137/0907087 [DOI] [Google Scholar]

[zoi180210r19] 19.Bach FR. Bolasso: model consistent Lasso estimation through the bootstrap. Paper presented at: Proceedings of the 25th International Conference on Machine Learning; July 5-9, 2008; Helsinki, Finland. [Google Scholar]

[zoi180210r20] 20.Laurin C, Boomsma D, Lubke G. The use of vector bootstrapping to improve variable selection precision in Lasso models. Stat Appl Genet Mol Biol. 2016;15(4):305-320. doi: 10.1515/sagmb-2015-0043 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r21] 21.Zhang J, Yu KF. What’s the relative risk? a method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998;280(19):1690-1691. doi: 10.1001/jama.280.19.1690 [DOI] [PubMed] [Google Scholar]

[zoi180210r22] 22.Moons KG, Altman DG, Reitsma JB, et al. . Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1-W73. doi: 10.7326/M14-0698 [DOI] [PubMed] [Google Scholar]

[zoi180210r23] 23.National Center for Cardiovascular Diseases Report on cardiovascular diseases in China 2014. Chin Circ J. 2015;(7):617-622. [Google Scholar]

[zoi180210r24] 24.Dreyer RP, Xu X, Zhang W, et al. . Return to work after acute myocardial infarction: comparison between young women and men. Circ Cardiovasc Qual Outcomes. 2016;9(2)(suppl 1):S45-S52. doi: 10.1161/CIRCOUTCOMES.115.002611 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r25] 25.Mirmohammadi SJ, Sadr-Bafghi SM, Mehrparvar AH, et al. . Evaluation of the return to work and its duration after myocardial infarction. ARYA Atheroscler. 2014;10(3):137-140. [PMC free article] [PubMed] [Google Scholar]

[zoi180210r26] 26.Thompson DR, Yu C-M. Cardiac rehabilitation: China In: Perk J, Mathes P, Gohlke H, et al. , eds. Cardiovascular Prevention and Rehabilitation. London, UK: Springer; 2007:48-51. doi: 10.1007/978-1-84628-502-8_10 [DOI] [Google Scholar]

[zoi180210r27] 27.Oldridge NB, Guyatt GH, Fischer ME, Rimm AA. Cardiac rehabilitation after myocardial infarction: combined experience of randomized clinical trials. JAMA. 1988;260(7):945-950. doi: 10.1001/jama.1988.03410070073031 [DOI] [PubMed] [Google Scholar]

[zoi180210r28] 28.Bittner V, Oberman A. Efficacy studies in coronary rehabilitation. Cardiol Clin. 1993;11(2):333-347. doi: 10.1016/S0733-8651(18)30183-8 [DOI] [PubMed] [Google Scholar]

[zoi180210r29] 29.Manion M. Retirement of Revolutionaries in China: Public Policies, Social Norms, Private Interests. Princeton, NJ: Princeton University Press; 2014. [Google Scholar]

[zoi180210r30] 30.Benjamin EJ, Virani SS, Callaway CW, et al. ; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee . Heart disease and stroke statistics—2018 update: a report from the American Heart Association [published correction appears in Circulation. 2018;137(12):e493]. Circulation. 2018;137(12):e67-e492. doi: 10.1161/CIR.0000000000000558 [DOI] [PubMed] [Google Scholar]

[zoi180210r31] 31.Mishra V, Smyth R. Working hours in Chinese enterprises: evidence from matched employer–employee data. Ind Relat J. 2013;44(1):57-77. doi: 10.1111/j.1468-2338.2012.00702.x [DOI] [Google Scholar]

[zoi180210r32] 32.Messenger JC, Lee S, McCann D. Working Time Around the World: Trends in Working Hours, Laws, and Policies in a Global Comparative Perspective. New York, NY: Taylor & Francis; 2007. [Google Scholar]

[zoi180210r33] 33.Zeng X, Lu L, Idris SU. . Working Time in Transition: The Dual Task of Standardization and Flexibilization in China, Conditions of Work and Employment Series No. 11. Geneva, Switzerland: International Labour Office; 2005. [Google Scholar]

[zoi180210r34] 34.de Jonge P, Zuidersma M, Bültmann U. The presence of a depressive episode predicts lower return to work rate after myocardial infarction. Gen Hosp Psychiatry. 2014;36(4):363-367. doi: 10.1016/j.genhosppsych.2014.03.006 [DOI] [PubMed] [Google Scholar]

[zoi180210r35] 35.Smolderen KG, Strait KM, Dreyer RP, et al. . Depressive symptoms in younger women and men with acute myocardial infarction: insights from the VIRGO study. J Am Heart Assoc. 2015;4(4):e001424. doi: 10.1161/JAHA.114.001424 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r36] 36.Dreyer RP, Wang Y, Strait KM, et al. . Gender differences in the trajectory of recovery in health status among young patients with acute myocardial infarction: results from the Variation in Recovery: Role of Gender on Outcomes of Young AMI Patients (VIRGO) Study. Circulation. 2015;131(22):1971-1980. doi: 10.1161/CIRCULATIONAHA.114.014503 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r37] 37.Kristofferzon ML, Löfmark R, Carlsson M. Myocardial infarction: gender differences in coping and social support. J Adv Nurs. 2003;44(4):360-374. doi: 10.1046/j.0309-2402.2003.02815.x [DOI] [PubMed] [Google Scholar]

[zoi180210r38] 38.Smedegaard L, Numé AK, Charlot M, Kragholm K, Gislason G, Hansen PR. Return to work and risk of subsequent detachment from employment after myocardial infarction: insights from Danish nationwide registries. J Am Heart Assoc. 2017;6(10):e006486. doi: 10.1161/JAHA.117.006486 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r39] 39.Campos-Serna J, Ronda-Pérez E, Artazcoz L, Moen BE, Benavides FG. Gender inequalities in occupational health related to the unequal distribution of working and employment conditions: a systematic review. Int J Equity Health. 2013;12:57. doi: 10.1186/1475-9276-12-57 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r40] 40.Reed GW, Rossi JE, Cannon CP. Acute myocardial infarction. Lancet. 2017;389(10065):197-210. doi: 10.1016/S0140-6736(16)30677-8 [DOI] [PubMed] [Google Scholar]

[zoi180210r41] 41.Wang Y, Eldridge N, Metersky ML, et al. . National trends in patient safety for four common conditions, 2005-2011. N Engl J Med. 2014;370(4):341-351. doi: 10.1056/NEJMsa1300991 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r42] 42.Wang Y, Eldridge N, Metersky ML, et al. . Association between hospital performance on patient safety and 30-day mortality and unplanned readmission for Medicare fee-for-service patients with acute myocardial infarction. J Am Heart Assoc. 2016;5(7):e003731. doi: 10.1161/JAHA.116.003731 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi180210r43] 43.Slebus FGJH, Peters RJ, Kuijer PP, Willems JH, Sluiter JK, Frings-Dresen MH. Factors Associated With Return to Work After Admission for Acute Coronary Syndrome: The Patient’s Perspective [dissertation]. Amsterdam, the Netherlands: University of Amsterdam; 2009. [Google Scholar]

[zoi180210r44] 44.National Bureau of Statistics of China Statistical Communiqué of the People’s Republic of China on the 2015 National Economic and Social Development. Beijing, China: China Statistics Press; 2016. [Google Scholar]

[zoi180210r45] 45.Wang S, Marquez P, Langenbrunner J. Toward a Healthy and Harmonious Life in China: Stemming the Rising Tide of Non-communicable Diseases. Washington, DC: World Bank; 2011. [Google Scholar]

[zoi180210r46] 46.Abbas AE, Brodie B, Stone G, et al. . Frequency of returning to work one and six months following percutaneous coronary intervention for acute myocardial infarction. Am J Cardiol. 2004;94(11):1403-1405. doi: 10.1016/j.amjcard.2004.08.014 [DOI] [PubMed] [Google Scholar]

PERMALINK

Factors Associated With Return to Work After Acute Myocardial Infarction in China

Zihan Jiang, MD

Rachel P Dreyer, PhD

John A Spertus, MD

Frederick A Masoudi, MD, MSPH

Jing Li, MD, PhD

Xin Zheng, MD, PhD

Xi Li, MD, PhD

Chaoqun Wu, MD, MS

Xueke Bai, MS

Shuang Hu, PhD

Yun Wang, PhD

Harlan M Krumholz, MD, SM

Hong Chen, MD

Abstract

Importance

Objectives

Design, Setting, and Participants

Main Outcomes and Measures

Results

Conclusions and Relevance

Trial Registration

Key Points

Question

Findings

Meaning

Introduction

Methods

Study Sample and Data Collection

Outcome

Patient and Hospital Characteristics

Statistical Analysis

Results

Baseline Patient Characteristics

Figure 1. Flowchart of Patient Enrollment.

Table 1. Comparison of Baseline Characteristics Between Patients Who Did and Patients Who Did Not Return to Work Within 12 Months After Acute Myocardial Infarction.

Returning to Work

Table 2. Baseline Patient Characteristics by Reason for Not Returning to Work.

Factors Associated with Returning to Work

Figure 2. Adjusted Risk Ratio (RR) of Returning to Work Within 12 Months After Discharge for Acute Myocardial Infarction.

Discussion

Implications

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases