Multimorbidity and its Associated Factors in Korean Shift Workers: Population-Based Cross-Sectional Study

被引:0
|
作者
Hong, Hye Chong [1 ]
Kim, Young Man [2 ,3 ,4 ]
机构
[1] Chung Ang Univ, Dept Nursing, Seoul, South Korea
[2] Jeonbuk Natl Univ, Coll Nursing, 567 Baekje-daero,Deokjin-gu, Jeonju 54896, South Korea
[3] Jeonbuk Natl Univ, Res Inst Nursing Sci, Jeonju, South Korea
[4] Jeonbuk Natl Univ Hosp, Biomed Res Inst, Jeonju, South Korea
来源
基金
新加坡国家研究基金会;
关键词
chronic disease; multimorbidity; shift work schedule; shift workers; population-based study; Korea; network analysis; logisticregression; cross-sectional study; public health; NATIONAL-HEALTH; SLEEP; RISK; PREVALENCE; NIGHT; EPIDEMIOLOGY; DISEASE; ADULTS; LIGHT;
D O I
10.2196/55014
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Multimorbidity is a crucial factor that influences premature death rates, poor health, depression, quality of life, and use of health care. Approximately one-fifth of the global workforce is involved in shift work, which is associated with increased risk for several chronic diseases and multimorbidity. About 12% to 14% of wage workers in Korea are shift workers. However, the prevalence of multimorbidity and its associated factors in Korean shift workers are rarely reported. Objective: This study aimed to assess multimorbidity prevalence, examine the factors associated with multimorbidity, and identify multimorbidity patterns among shift workers in Korea. Methods: This study is a population-based cross-sectional study using Korea National Health and Nutrition Examination Survey data from 2016 to 2020. The study included 1704 (weighted n=2,697,228) Korean shift workers aged 19 years and older. Multimorbidity was defined as participants having 2 or more chronic diseases. Demographic and job-related variables, including regular work status, average working hours per week, and shift work type, as well as health behaviors, including BMI, smoking status, alcohol use, physical activity, and sleep duration, were included in the analysis. A survey-corrected logistic regression analysis was performed to identify factors influencing multi morbidity among the workers, and multimorbidity patterns were identified with a network analysis. Results: The overall prevalence of multimorbidity was 13.7% (302/1704). Logistic regression indicated that age, income, regularwork, and obesity were significant factors influencing multimorbidity. Network analysis results revealed that chronic diseasesclustered into three groups: (1) cardiometabolic multimorbidity (hypertension, dyslipidemia, diabetes, coronary heart disease,and stroke), (2) musculoskeletal multimorbidity (arthritis and osteoporosis), and (3) unclassified diseases (depression, chronicliver disease, thyroid disease, asthma, cancer, and chronic kidney disease). Conclusions: The findings revealed that several socioeconomic and behavioral factors were associated with multimorbidity among shift workers, indicating the need for policy development related to work schedule modification. Further organization-level screening and intervention programs are needed to prevent and manage multimorbidity among shift workers. We also recommend longitudinal studies to confirm the effects of job-related factors and health behaviors on multimorbidity among shift workers in the future.
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页数:15
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