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Review| Volume 135, P37-49, May 2023

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A systematic review and meta-analysis of risk factors associated with healthcare-associated infections among hospitalized patients in Chinese general hospitals from 2001 to2022

  • X. Liu
    Correspondence
    Corresponding author. Address: Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
    Affiliations
    Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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  • Y. Long
    Affiliations
    Global Health Institute/School of Health Sciences, Wuhan University, Wuhan, China
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  • C. Greenhalgh
    Affiliations
    Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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  • S. Steeg
    Affiliations
    Division of Psychology and Mental Health, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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  • J. Wilkinson
    Affiliations
    Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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  • H. Li
    Affiliations
    Global Health Institute/School of Health Sciences, Wuhan University, Wuhan, China
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  • A. Verma
    Affiliations
    Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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  • A. Spencer
    Affiliations
    Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, UK
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Open AccessPublished:March 10, 2023DOI:https://doi.org/10.1016/j.jhin.2023.02.013

      Summary

      Background

      Healthcare-associated infections (HAIs) are a serious global public health issue. However, a comprehensive analysis of risk factors for HAIs has yet been undertaken at a large scale among general hospitals in China. The aim of this review was to assess risk factors associated with HAIs in Chinese general hospitals.

      Methods

      Medline, EMBASE and Chinese Journals Online databases were searched to find studies published from 1st January 2001 to 31st May 2022. The random-effects model was used to estimate odds ratio (OR). Heterogeneity was assessed based on the τˆ2 and I2 statistics.

      Results

      A total of 5037 published papers were identified from the initial search and 58 studies were included in the quantitative meta-analysis; 1,211,117 hospitalized patients were incorporated covering 41 regions in 23 provinces of China and 29,737 were identified as having HAIs. Our review showed that HAIs were significantly associated with sociodemographic characteristics including age older than 60 years (OR: 1.74 (1.38–2.19)) and male sex (1.33 (1.20–1.47)); invasive procedures (3.54 (1.50–8.34)); health conditions such as chronic diseases (1.49 (1.22–1.82)), coma (OR: 5.12 (1.70–15.38)) and immunosuppression (2.45 (1.55–3.87)). Other risk factors included long-term bed (5.84 (5.12–6.66)), and healthcare-related risk factors such as chemotherapy (1.96 (1.28–3.01)), haemodialysis (3.12 (1.80–5.39)), hormone therapy (2.96(1.96–4.45)), immunosuppression (2.45 (1.55–3.87)) and use of antibiotics (6.64 (3.16–13.96)), and longer than 15 hospitalization days (13.36 (6.80–26.26)).

      Conclusions

      Being male and aged over 60 years, invasive procedure, health conditions, healthcare-related risk factors, and longer than 15 hospitalization days were the main risk factors associated with HAIs in Chinese general hospitals. This supports the evidence base to inform the relevant cost-effective prevention and control strategies.

      Keywords

      Introduction

      Healthcare-associated infections (HAIs) are defined as infections acquired by patients after admittance to a hospital or other healthcare facility for more than 48 h, which were not present or incubating at the time of admission. HAIs can appear during hospital stay or after discharge. They include occupational infections among health professionals [

      World Health Organization. Health care-associated infections FACT SHEET 2011. Available at: https://www.who.int/gpsc/country_work/gpsc_ccisc_fact_sheet_en.pdf. [last accessed June 2021].

      ]. HAIs are a serious global public health issue, having a great impact on patient safety and disease burden [
      • Allegranzi B.
      • Nejad S.B.
      • Combescure C.
      • Graafmans W.
      • Attar H.
      • Donaldson L.
      • et al.
      Burden of endemic health-care-associated infection in developing countries: systematic review and meta-analysis.
      ,
      • Bagheri Nejad S.
      • Allegranzi B.
      • Syed S.B.
      • Ellis B.
      • Pittet D.
      Health-care-associated infection in Africa: a systematic review.
      ,
      • Cassini A.
      • Plachouras D.
      • Eckmanns T.
      • Abu Sin M.
      • Blank H.P.
      • Ducomble T.
      • et al.
      Burden of six healthcare-associated infections on European population health: estimating incidence-based disability-adjusted life years through a population prevalence-based modelling study.
      ,
      • Irek E.O.
      • Amupitan A.A.
      • Obadare T.O.
      • Aboderin A.O.
      A systematic review of healthcare-associated infections in Africa: An antimicrobial resistance perspective.
      ,
      • Zimlichman E.
      • Henderson D.
      • Tamir O.
      • Franz C.
      • Song P.
      • Yamin C.K.
      • et al.
      Health care-associated infections: a meta-analysis of costs and financial impact on the US health care system.
      ]. HAIs are associated with increased risks of mortality and morbidity, longer length of hospitalization and high economic burden [
      • Cai Y.
      • Venkatachalam I.
      • Tee N.W.
      • Tan T.Y.
      • Kurup A.
      • Wong S.Y.
      • et al.
      Prevalence of healthcare-associated infections and antimicrobial use among adult inpatients in Singapore acute-care hospitals: results from the first national point prevalence survey.
      ,
      • Li H.
      • Liu X.
      • Cui D.
      • Wang Q.
      • Mao Z.
      • Fang L.
      • et al.
      Estimating the direct medical economic burden of health care-associated infections in public tertiary hospitals in Hubei Province, China.
      ,
      • Lv Y.
      • Chen L.
      • Yu J.W.
      • Xiang Q.
      • Tang Q.S.
      • Wang F.D.
      • et al.
      Hospitalization costs due to healthcare-associated infections: an analysis of propensity score matching.
      ,

      Toscano C. Costs of healthcare associated infections in countries the Latina American and Caribbean Region: A Systematic Literature Review 2017. Available at: https://www.paho.org/hq/index.php?option=com_docman&view=download&category_slug=webinar-materias-presentations-9016&alias=39269-costs-healthcare-associated-infections-countries-latina-american-caribbean-region-april-2017-269&Itemid=270&lang=en. [last accessed June 2021].

      ]. In the USA, 9000 deaths attributable to HAIs were estimated from 1990 to 2002, resulting in a cost of US$ 28 to US$ 45 billion per year [
      • Stone P.W.
      Economic burden of healthcare-associated infections: An American perspective.
      ]. In addition, HAIs are one of the key drivers of the increase in occurrence of antimicrobial resistance (AMR) making infections more complex to treat [
      • Hansen S.
      • Schwab F.
      • Zingg W.
      • Gastmeier P.
      Process and outcome indicators for infection control and prevention in European acute care hospitals in 2011 to 2012 – Results of the PROHIBIT study.
      ].
      The HAI prevalence of hospitalized patients at any given time in developing countries is 10%, while it is less at 7% in developed countries reported by the World Health Organization (WHO) [

      World Health Organization. Health care-associated infections FACT SHEET 2011. Available at: https://www.who.int/gpsc/country_work/gpsc_ccisc_fact_sheet_en.pdf. [last accessed June 2021].

      ]. The risk of HAIs in developing countries is reported to be between two and 20 times higher than that in developed countries [

      World Health Organization. Health care-associated infections FACT SHEET 2011. Available at: https://www.who.int/gpsc/country_work/gpsc_ccisc_fact_sheet_en.pdf. [last accessed June 2021].

      ]. China is one of the developing countries seriously affected by HAIs. Our previous systematic review and meta-analysis reported that the additional direct economic burden attributable to HAIs estimated by the total medical expenditure, the medicine expenditure and hospitalization days per inpatient was ¥24,881.37, ¥9,438.46 and 13.89 days in Chinese general hospitals [
      • Liu X.
      • Spencer A.
      • Long Y.
      • Greenhalgh C.
      • Steeg S.
      • Verma A.
      A systematic review and meta-analysis of disease burden of healthcare-associated infections in China: an economic burden perspective from general hospitals.
      ].
      Risk factors analysis is one way to help health professionals understand the factors associated with the development of HAIs and inform the creation of effective infection control programmes, guidelines and regulations. A risk factor in our study is defined as an aspect of individual behaviour or lifestyle, environmental exposure, inborn or inherited characteristics associated with an increased occurrence of a disease. Risk factors including age over 85 years, hospitalization in intensive care units (ICUs) and indwelling devices are associated with an increase in the occurrence of HAIs [
      • Zhang Y.
      • Zhang J.
      • Wei D.
      • Yang Z.
      • Wang Y.
      • Yao Z.
      Annual surveys for point-prevalence of healthcare-associated infection in a tertiary hospital in Beijing, China, 2012-2014.
      ]. Also, patients who have received antimicrobials or experienced central vascular catheters are also shown to be more likely to acquire HAIs [
      • Yallew W.W.
      • Kumie A.
      • Yehuala F.M.
      Risk factors for hospital-acquired infections in teaching hospitals of Amhara regional state, Ethiopia: A matched-case control study.
      ]. It is essential to identify risk factors for HAIs, so as to inform the policy makers and hospital managers to make effective prevention and control measures to reduce the occurrence of HAIs, thereby reducing mortality, morbidity, and economic burden, and allocation of the relevant medical resources to protect vulnerable patients from acquiring HAIs.
      Wang et al. conducted a systematic review and meta-analysis and reported the pooled prevalence of HAIs in mainland China was 3.12% in 2018 [
      • Wang J.
      • Liu F.
      • Tartari E.
      • Huang J.
      • Harbarth S.
      • Pittet D.
      • et al.
      The prevalence of healthcare-associated infections in mainland China: a systematic review and meta-analysis.
      ]. In the same year, the total population of China was 1.4 billion [

      Population, China. 2018. Available at: https://data.worldbank.org/indicator/SP.POP.TOTL?intcid=ecr_hp_BeltD_en_ext&locations=CN. [last accessed December 2022].

      ] and the national hospitalization rate among people presenting at hospital was 18.2% [
      National Health Commission of the people's Republic of China
      2019 China health statistics yearbook.
      ]. Therefore, the total number of hospitalized patients with HAIs was estimated to be 7.95 million. Understanding the risk factors for HAIs is especially important in China for corresponding prevention and control measures, because the number of hospitalized patients with HAIs is large and 35–55% of HAIs can be prevented [
      • Schreiber P.W.
      • Sax H.
      • Wolfensberger A.
      • Clack L.
      • Kuster S.P.
      The preventable proportion of healthcare-associated infections 2005-2016: Systematic review and meta-analysis.
      ]. Several risk-factor analyses for HAIs studies have been conducted in China. However, all of them were single-centre studies. Only one systematic review and meta-analysis on risk factors associated with HAIs among tuberculosis hospitalized patients has been undertaken in Chinese hospitals [
      • Liu X.L.
      • Ren N.L.
      • Ma Z.F.
      • Zhong M.L.
      • Li H.
      Risk factors on healthcare-associated infections among tuberculosis hospitalized patients in China from 2001 to 2020: a systematic review and meta-analysis.
      ]. A comprehensive analysis of risk factors for HAIs has yet to be undertaken at a large scale in China. The types of hospitals are categorized into general hospitals, speciality hospitals, traditional Chinese medicine hospitals, hospitals of integrated traditional Chinese and western medicine, ethnic medical hospitals, and nursing care hospitals. By the end of 2021, the number of general hospitals was 20,307, accounting for 55.3% of the overall hospitals [
      National Health Commission of the People's Republic of China
      2022 China health statistics yearbook [in Chinese].
      ]. Therefore, the aim of this systematic review and meta-analysis was to assess the risk factors associated with HAIs between hospitalized patients with HAIs and those without HAIs in Chinese general hospitals. General hospitals refer to large hospitals with a resident medical staff which provide continuous care to maternity, surgical and medical patients. They are different from the specialty hospitals, such as maternity hospitals, and are classified into three levels, including primary, secondary and tertiary hospitals [
      • Liu X.
      • Spencer A.
      • Long Y.
      • Greenhalgh C.
      • Steeg S.
      • Verma A.
      A systematic review and meta-analysis of disease burden of healthcare-associated infections in China: an economic burden perspective from general hospitals.
      ].

      Methods

      Systematic search strategy

      The PICO/S (Population, Intervention, Comparison, Outcome/Study type) tool was deployed and modified to define the scope of the literature, as follows. Population: hospitalized patients admitted to Chinese general hospitals for more than 48 h. Exposure: any potential risk factor which many have an impact on HAIs, defined by the Ministry of Health, China in 2001 [

      Ministry of Health. Diagnostic criteria of nosocomial infection [in Chinese] 2001. Available at: http://www.nhfpc.gov.cn/yzygj/s3593/200804/e19e4448378643a09913ccf2a055c79d.shtml. [last accessed June 2021].

      ]. Comparison: hospitalized patients without HAIs. Outcome: HAIs. Study type: cross-sectional, case–control, or cohort study.
      The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines were applied to guide our systematic review and meta-analysis. We selected Medline, EMBASE and Chinese Journals Online databases (China National Knowledge Infrastructure (CNKI), Chinese Wan Fang digital database and Chinese Science and Technique Journals Database (VIP)) as our main databases to search the relevant articles. The studies published were limited to between 1st January 2001 and 31st May 2022.
      Medical subject heading (MeSH) terms were used as the keywords in Medline and EMBASE databases to search the studies published in English. The MeSH terms were “cross infection/healthcare-associated infections/hospital acquired infections” AND “risk factors” AND “China”. Terms searched in the title, abstract and keywords included “healthcare-associated infections/hospital acquired infections/hospital infections/nosocomial infections”, “risk factors/influencing factors”, and “China” for the Chinese databases with corresponding Chinese, and the logic word “AND” was used with these search terms.

      Inclusion and exclusion criteria

      The inclusion criteria included: (1) observational studies including a case–control, cohort study, or cross-sectional design; (2) a multi-centre or a single-centre study; (3) studies published in either English or Chinese; (4) studies conducted in a general hospital rather than a specialty hospital; (5) any studies published between 1st January 2001 and 31st May 2022; (6) studies conducted in China.
      The exclusion criteria included: (1) conference papers, editorials, or letters; (2) studies using repeated data; (3) studies conducted in specific hospitals (e.g., maternal and paediatric hospitals), or units (e.g., neurosurgery), or disease (e.g., pneumonia), or patients (e.g., old patients or infants), or infection type (e.g., ventilator-associated pneumonia); (4) studies only describing the prevalence of HAIs; (5) studies only describing the characteristics of risk factors from the perspectives of health professionals; (6) studies which did not define HAIs corresponding to the definition developed by Ministry of Health, China in 2001 [

      Ministry of Health. Diagnostic criteria of nosocomial infection [in Chinese] 2001. Available at: http://www.nhfpc.gov.cn/yzygj/s3593/200804/e19e4448378643a09913ccf2a055c79d.shtml. [last accessed June 2021].

      ]); (7) studies not providing the specific data and only providing the statistical conclusion.

      Data abstraction

      X.L. and Y.L., the two independent reviewers, each first searched the relevant literature on risk factors associated with HAIs from the databases through keywords, titles and abstracts. Then, both of the reviewers independently screened the eligibility of the searched literature based on the inclusion and exclusion criteria. Both reviewers checked 10% of the studies included by the other reviewer to determine the eligibility. Disagreement on the included studies was resolved by discussion between the two independent reviewers.

      Quality assessment

      Two independent researchers (X.L. and Y.L.) conducted the quality assessment of the included studies according to the criteria proposed by the Joanna Briggs Institute (JBI) critical appraisal tools for cross-section, case–control and cohort study checklist [

      The University of Adelaide. Critical Appraisal Tools 2020. Available at: https://jbi.global/critical-appraisal-tools. [last accessed July 2021].

      ]. Eight questions for a cross-sectional study, 10 questions for a case–control study, and 11 questions for a cohort study were used to assess the quality. For each question, four options (Yes, Unclear, No and Not applicable) were provided for singe choice. A value was assigned to each answer, including a range from 0 to 2 points. For example, 2 points were assigned if the answer was “Yes”. Therefore, the full points were 16 for a cross-sectional study, while 16, 20 and 22 points were full for a cross-sectional study, a case–control study and a cohort study, respectively. Higher-quality studies, therefore, scored more highly.

      Statistical analysis

      STATA 14.0 software was employed to estimate the pooled unadjusted odds ratios (OR) of the potential risk factors associated with HAIs with 95% confidence intervals (95% CIs) by extracting the portions of potential risk factors between patients with HAIs and patients without HAIs from the included studies. Heterogeneity among studies was assessed based on the τˆ2 and I2 statistics and results with a τˆ2 (P<0.05) and/or I2 >50% were considered as heterogeneity existing among studies. A random-effects model and a Forest plot were used to estimate the pooled OR values. The statistical significance level was set at P<0.05. A funnel plot was presented to show the publication bias among the included studies. Subgroup analyses were undertaken to investigate whether year of study (before and after 2013, when considerable changes to the medical care system in China occurred) and location of setting (non-provincial and provincial capitals) had an impact on potential risk factors associated with HAIs.

      Results

      Characteristics of eligible studies

      Figure 1 shows that a total of 5037 published papers were identified from the database search. After screening the full text with the inclusion and exclusion criteria, 58 publications were included in the quantitative synthesis and meta-analysis for the potential risk factors associated with HAIs.
      Figure 1
      Figure 1Flow diagram of literature search. CNKI, China National Knowledge Infrastructure; HAI, healthcare-associated infection; VIP, Chinese Science and Technique Journals Database; Wangfang database, Chinese Wan Fang digital database.

      Characteristics: synthesis of the included studies

      Table I shows that a total of 1,211,117 hospitalized patients were incorporated in the 58 included studies, which covered 41 regions in 23 provinces (34 provincial administrative regions in total) in China. Of them, 29,737 hospitalized patients were identified as having HAIs, and 1,181,380 hospitalized patients were without HAIs. Most of the included studies (52 out of 58) were cross-sectional studies, while just five studies adopted a case–control design [
      • Yin J.
      Study on the incidence and risk factors of nosocomial infection in a hospital in xi'an [in Chinese].
      ,
      • Xu N.
      • Li Y.
      • Chen J.
      • Xu W.
      • Wang X.
      Case-control study on risk factors for healthcare-associated infections [in Chinese].
      ,
      • Gao Z.
      • Wang J.
      • Li Y.
      Relevant risk factor analysis for healthcare-associated infections from 2009 to 2011.
      ,
      • Fu R.
      • Yuan D.
      Risk factor analysis and pathogenic bacteria distribution on healthcare-associated infections among 276 hospitalised patients [in Chinese].
      ,
      • Li W.
      Study on the characteristics and risk factors of nosocomial infections in a comprehensive hospital [in Chinese].
      ]. Only one study was a cohort study [
      • Huang H.
      • Xu N.
      • Lian X.
      • Qiu L.
      Retrospective cohort study on risk factors for healthcare-associated infections [in Chinese].
      ]. The majority of the studies (56 of 58) were conducted in tertiary hospitals and all of the general hospitals were located in cities. Only one study was a multi-centre study [
      • Fu T.
      • Wei S.
      • Huang L.
      • Yang J.
      • Zhan C.
      Cross-sectional survey of prevalence of nosocomial infections in tertiary hospitals of Sanya and analysis of risk factors [in Chinese].
      ].
      Table ICharacteristics of the studies included conducted in Chinese general hospitals from 2001 to 2022
      Study IDAuthor (year) [ref. no.]Study designCity (province)Study settingYear begun and duration (years)Number of participants
      HAIsNon-HAIs
      An et al. (2002) [
      • An W.
      • Tan J.
      • Cao L.
      Point prevalence survey on healthcare-associated infections [in Chinese].
      ]
      Retrospective cross-sectionalZunyi (Guizhou)-0One tertiary hospital2001, 1 day31481
      1Chen et al. (2002) [
      • Chen J.
      • Yang J.
      • Wang C.
      • Chen D.
      • He J.
      • Zhou Z.
      • et al.
      Cross-sectional study on healthcare-associated infections among 726 hospitalised patients [in Chinese].
      ]
      Retrospective cross-sectionalGuiyang (Guizhou)-1One tertiary hospital2001, 1 day53643
      2Dai et al. (2002) [
      • Dai D.
      • Shui R.
      • Chen Q.
      Point prevalence survey on healthcare-associated infections in a hospital [in Chinese].
      ]
      Retrospective cross-sectionalTaizhou (Zhejiang)-0One tertiary hospital2001, 1 day66844
      3Shu et al. (2005) [
      • Shu M.
      • Wang Z.
      • Zhuang H.
      • Wang X.
      • Wang X.
      Influencing factor investigation on healthcare-associated infections among 258 hospitalised patients [in Chinese].
      ]
      Retrospective cross-sectionalChengdu (Sichuan)-1One tertiary hospital2003, 1 month2584358
      4Xu et al. (2005) [
      • Xu N.
      • Li Y.
      • Chen J.
      • Xu W.
      • Wang X.
      Case-control study on risk factors for healthcare-associated infections [in Chinese].
      ]
      Retrospective case-controlFuzhou (Fujian)-1One tertiary hospital2002, 172144
      5Yang (2005) [
      • Yang Z.
      Report on surveillance of healthcare-associated infections [in Chinese].
      ]
      Retrospective cross-sectionalTangshan (Hebei)–One secondary hospital2002, 21643779
      6Zhang et al. (2005) [
      • Zhang M.
      • Yan J.
      • Shang L.
      • Yan H.
      • Yang Z.
      • Lei Q.
      Survey and analysis on influencing factors for healthcare-associated infections [in Chinese].
      ]
      Retrospective cross-sectionalUrumchi (Xinjiang)One tertiary hospital2004, 134313,775
      7Wang et al. (2006) [
      • Wang J.
      • Wu X.
      • Li Y.
      • Wang J.
      Point prevalence survey on healthcare-associated infections for 3 years [in Chinese].
      ]
      Retrospective cross-sectionalShaoguan (Guangdong)One tertiary hospital2002–2005, 3 days1732170
      8Huang et al. (2007) [
      • Huang H.
      • Xu N.
      • Lian X.
      • Qiu L.
      Retrospective cohort study on risk factors for healthcare-associated infections [in Chinese].
      ]
      Retrospective cohortXiamen (Fujian)One tertiary hospital2005, 188962
      9Huang (2007) [
      • Huang Q.
      Findings and analysis for point prevalence survey on healthcare-associated infections [in Chinese].
      ]
      Retrospective cross-sectionalWenling (Zhejiang)One tertiary hospital2005, 1 day67898
      10Chen et al. (2008) [
      • Chen M.
      • Ai B.
      • Duan L.
      • Zhu L.
      • Wen H.
      Survey and risk factor analysis on healthcare-associated infections [in Chinese].
      ]
      Retrospective cross-sectionalJingzhou (Hunan)One tertiary hospital2007, 6 months36913,151
      11Hong et al. (2009) [
      • Hong B.
      • Han X.
      • Zhang W.
      • Li L.
      • Wang L.
      • Jing L.
      • et al.
      Survey and analysis on healthcare-associated infections in a hospital [in Chinese].
      ]
      Retrospective cross-sectionalBaoji (Shaanxi)One tertiary hospital2008, 1 day15712
      12Fan et al. (2010) [
      • Fan S.
      • Jin X.
      • Lv G.
      • Xu W.
      • Ge W.
      • Mu C.
      Investigation on nosocomial infection prevalence and risk factors in a comprehensive hospital [in Chinese].
      ]
      Retrospective cross-sectionalXi'an (Shaanxi)One tertiary hospital2009, 1 day741691
      13He (2011) [
      • He M.
      Nursing interventions and risk factor analysis on healthcare-associated infections among hospitalised patients [in Chinese].
      ]
      Retrospective cross-sectionalZhangjiagang (Jiangsu)One secondary hospital2008, 11241156
      14Zhang et al. (2011) [
      • Zhang J.
      • Lu P.
      • Zhou W.
      Point prevalence survey on healthcare-associated infections among hospitalised patients [in Chinese].
      ]
      Retrospective cross-sectionalSuzhou (Jiangsu)One tertiary hospital2009–2010, 2 days811790
      15Gao et al. (2011) [
      • Gao Z.
      • Wang J.
      • Li Y.
      Relevant risk factor analysis for healthcare-associated infections from 2009 to 2011.
      ]
      Retrospective case-controlChangchun (Jilin)One tertiary hospital2009, 376913,768
      16Tan (2012) [
      • Tan X.
      A study on current status and risk factors of nosocomial infection in an affiliated hospital of some university [in Chinese].
      ]
      Retrospective cross-sectionalGuangzhou (Guangdong)One tertiary hospital2009–2011, 3 days2555176
      17Yu et al. (2013) [
      • Yu H.
      • Liu Y.
      • Yang H.
      Risk factor analysis and point prevalence survey on healthcare-associated infections [in Chinese].
      ]
      Retrospective cross-sectionalShanghaiOne tertiary hospital2012, 1 day311343
      18Fu & Yuan (2013) [
      • Fu R.
      • Yuan D.
      Risk factor analysis and pathogenic bacteria distribution on healthcare-associated infections among 276 hospitalised patients [in Chinese].
      ]
      Retrospective case-controlShaoxing (Zhejiang)One tertiary hospital2011, 12766051
      19Hu (2013) [
      • Hu C.
      Point prevalence survey on healthcare-associated infections from 2010 to 2012 [in Chinese].
      ]
      Retrospective cross-sectionalZhangjiajie (Hunan)One tertiary hospital2010–2012, 3 days572288
      20Tang et al. (2014) [
      • Tang Y.
      • Chen L.
      • Sun R.
      • Tan M.
      Influencing factor analysis and point prevalence survey on healthcare-associated infections in 20113 of a hospital [in Chinese].
      ]
      Retrospective cross-sectionalYibin (Sichuan)One tertiary hospital2013, 1 day551760
      21Peng et al. (2014) [
      • Peng M.
      • Zhou J.
      • Jiang S.
      • Liu T.
      • Dai Y.
      • Feng C.
      Risk factor analysis and cross-sectional study on healthcare-associated infections in a tertiary A class general hospital in 2013 [in Chinese].
      ]
      Retrospective cross-sectionalChangzhou (Jiangsu)One tertiary hospital2013, 1 day992029
      22Li et al. (2014) [
      • Li Q.
      • Ping B.
      • Li B.
      Risk factor analysis and point prevalence survey on healthcare-associated infections in 2013 [in Chinese].
      ]
      Retrospective cross-sectionalXi'an (Shaanxi)One tertiary hospital2013, 1 day1042134
      23Wang (2014) [
      • Wang J.
      Survey and analysis on healthcare-associated infections from 2011 to 2013 [in Chinese].
      ]
      Retrospective and prospective cross-sectionalHefei (Anhui)One tertiary hospital2011, 3261197,114
      24Zhao & Xuan (2014) [
      • Zhao H.
      • Xuan K.
      Report of point prevalence survey on healthcare-associated infections among hospitalised patients [in Chinese].
      ]
      Retrospective cross-sectionalLuohe (Hebei)One tertiary hospital2012, 1 day42990
      25Hu (2014) [
      • Hu M.
      Report of point prevalence survey on healthcare-associated infections for 3 years in a hospital [in Chinese].
      ]
      Retrospective cross-sectionalNanning (Guangxi)One tertiary hospital2011–2013, 3 days1352877
      26Li et al.-1 (2014) [
      • Li M.
      • Lin J.
      • Zheng L.
      • Liu J.
      Point prevalence survey on healthcare-associated infections among hospitalised patients in a hospital [in Chinese].
      ]
      Retrospective cross-sectionalWenzhou (Zhejiang)One tertiary hospital2013,1 day1931805
      27Zhu (2014) [
      • Zhu H.
      The study on current status of hospital infection and hazard factors in a general hospital in 2012 [in Chinese].
      ]
      Retrospective cross-sectionalTianjinOne tertiary hospital2012, 169944,669
      28Wu (2014) [
      • Wu R.
      Comprehensive hospitals nosocomial infections trends and risk factors [in Chinese].
      ]
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      Description of the potential risk factors among the included studies

      Table II shows that a total of 58 potential risk factors were identified from the included studies. The most frequent potential risk factors studied were age (48 of 58), indwelling urinary catheter (46 of 58), surgery (42 of 58), gender (41 of 58), ventilator (41 of 58), and arteriovenous cannula (34 of 58). Potential risk factors of which the frequency was less than 2 were not included in the following meta-analyses. In addition, because the classification of season confirming HAIs and hospital wards was not consistent in the included studies, neither were included in the meta-analyses. Although the classification of the age and length of hospitalization was different among the included studies, we adopted the most frequent classification of the age and length of hospitalization in the meta-analyses.
      Table IIFrequency of the potential risk factors identified among the included studies from 2010 to 2022
      Potential risk factors/Study ID123456789101112131415161718192021222324252627282930
      1Age
      2Alcohol
      3Arteriovenous cannula
      4Artificial devices
      5Blood transfusion
      6Body Mass Index (BMI)
      7Cardiovascular and cerebrovascular diseases
      8Central/Peripheral arteriovenous catheter
      9Chemotherapy
      10Chronic diseases
      11Chronic diseases or low immunity
      12Clinical diagnosis
      13Coma
      14Deep vein catheterization
      15Diabetes mellitus
      16Disease of blood system
      17Drainage
      18Endoscope
      19Foreign matter implantation
      20Gastric tube
      21Gender
      22General anaesthesia
      23Glucocorticoids
      24Haemodialysis
      25Health expenses
      26Hormone
      27Hypertension
      28Immunosuppression
      29Impaired consciousness
      30Indwelling central catheter
      31Indwelling urinary catheter
      32Infection when admitted
      33Intravenous catheterization
      34Intravenous infusion
      35Invasive procedures
      36Length of hospitalization
      37Liver cirrhosis
      38Long-term bed
      39Malignant tumour
      40Marriage
      41Mechanical ventilation
      42Nephropathy
      43Organ transplantation
      44Paracentesis
      45Parenteral nutrition
      46Personality
      47Previous disease history
      48Radiotherapy
      49Season of confirming HAIs
      50Smoking
      51Sulks
      52Surgery
      53Tracheal cannula
      54Tracheotomy
      55Underlying diseases
      56Use of antibiotics
      57Ventilator
      58Wards
      31323334353637383940414243444546474849505152535455565758Total
      48
      1
      34
      1
      1
      1
      1
      1
      19
      2
      1
      1
      5
      3
      8
      2
      3
      1
      1
      1
      41
      1
      4
      12
      1
      12
      1
      20
      1
      7
      46
      3
      1
      2
      9
      25
      3
      2
      7
      1
      4
      1
      1
      1
      1
      1
      1
      16
      3
      1
      1
      42
      7
      27
      7
      17
      41
      9
      Long-term bed refers to a patient who is on bed for a long period. Personality refers to a characteristic of a person. In our review, the personality was classified into three types, including extrovert, introvert, and neutral. Sulks mean that a person is silent and bad-tempered due to depression or being upset.

      Quality analysis of all the included studies

      As to the 52 cross-sectional studies, the average points were 11.69 ± 1.65, which indicated the quality of the included cross-sectional studies was moderate (11.69 of 16). The five case–control studies were of high quality, scoring from 18 to 19. The cohort study was assessed as scoring 15, which indicated moderate quality. This cohort study did not mention any information about the follow-up design. Chi-squared test or binary logistic regression was used to infer the statistical significance. However, it was not always clear whether unadjusted or adjusted ORs were reported from the binary logistic regression, although most of the included studies appeared to adopt the adjusted ORs according to the results. Quality assessments of the included studies are exhibited in the supplementary material (Supplementary Tables S1, S2 and S3).

      Meta-analyses of all the potential risk factors

      As shown in Table III, 31 potential risk factors were included in the meta-analyses. Most of the potential risk factors (27 of 31), except chronic diseases, infection when admitted, intravenous infusion, and liver cirrhosis, had a high heterogeneity (I2 ≥50%) among the studies. Our systematic review and meta-analysis showed that HAIs in China were significantly associated with age older than 60 years (OR: 1.74 (1.38–2.19)) and male sex (OR: 1.33 (1.20, 1.47)), invasive procedure (OR: 3.54 (1.50–8.34)), including arteriovenous cannula (OR: 3.73 (2.79–4.99)), deep vein catheterization (OR: 7.57 (1.03–55.91)), drainage (OR: 2.84 (1.93–4.20)), indwelling central catheter (OR: 6.79 (4.78–9.65)), indwelling urinary catheter (OR: 3.58 (2.75–4.66)), intravenous infusion (OR: 2.84 (1.72–4.67)), mechanical ventilation (OR: 4.59 (2.08–10.16)), surgery (OR: 1.64 (1.39–1.94)), tracheal cannula (OR: 5.35 (3.53–8.11)), tracheotomy (OR: 10.44 (7.50–14.53)) and ventilator (OR: 6.63 (5.41–8.11)), health conditions such as chronic diseases (OR: 1.49 (1.22–1.82)), coma (OR: 5.12 (1.70–15.38)), diabetes mellitus (OR: 2.29 (1.21–4.32)) and long-term bed stay (OR: 5.84 (5.12–6.66)), healthcare-related risk factors including chemotherapy (OR: 1.96 (1.28–3.01)), haemodialysis (OR: 3.12 (1.80–5.39)), hormone therapy (OR: 2.96 (1.96–4.45)), immunosuppression (OR: 2.45 (1.55–3.87)), more than three underlying diseases (OR: 2.63 (1.71–4.06)) and use of antibiotics (OR: 6.64 (3.16–13.96)), and longer than 15 hospitalization days (OR: 13.36 (6.80–26.26)). All the P-values were less than 0.05. The specific information about the Forest plots of the risk factors is presented in the Supplementary data. Moreover, the publication bias with the funnel plots is also shown in the Supplementary data and indicates that publication bias was presented among all included studies for each of the listed risk factors. Furthermore, the subgroup analyses by year and capital cities were also shown in the Supplementary data. Except for some risk factors, including hormone therapy, invasive procedure (indwelling central catheter, tracheotomy, ventilator), length of hospitalization, and use of antibiotics, the OR values were similar.
      Table IIIThe pooled odds ratios (ORs) of the potential risk factors estimated in the meta-analyses between patients with healthcare-associated infections (HAIs) and patients without HAIs
      Risk factorsOR [95% CI]τˆ2(P)Ι2 (%)P
      Age (≥60 years vs. <60 years)1.74 [1.38–2.19]0.2858 (<0.001)96.2<0.001∗
      Arteriovenous cannula3.73 [2.79–4.99]0.6374 (<0.001)97.4<0.001∗
      Chemotherapy1.96 [1.28–3.01]0.5559 (<0.001)98.10.002∗
      Chronic diseases1.49 [1.22–1.82]0.0000 (0.582)0.0<0.001∗
      Coma5.12 [1.70–15.38]1.5127 (<0.001)98.30.004∗
      Deep vein catheterization7.57 [1.03–55.91]2.7531 ((<0.001)90.40.047∗
      Diabetes mellitus2.29 [1.21–4.32]0.7683 (<0.001)97.20.011∗
      Disease of blood system12.91 [0.20–849.53]9.0882 (<0.001)99.60.231
      Drainage2.84 [1.93–4.20]0.0918 (0.003)79.0<0.001∗
      Gender (Male vs. Female)1.33 [1.20,1.47]0.0724 (<0.001)82.5<0.001∗
      Glucocorticoids2.00 [0.96–4.14]0.3683 (0.014)71.60.063
      Haemodialysis3.12 [1.80–5.39]0.4825 (<0.001)74.2<0.001∗
      Hormone2.96 [1.96–4.45]0.3357 (<0.001)91.3<0.001∗
      Immunosuppression2.45 [1.55–3.87]0.7765 (<0.001)97.5<0.001∗
      Indwelling central catheter6.79 [4.78–9.65]0.1520 (<0.001)84.2<0.001∗
      Indwelling urinary catheter3.58 [2.75–4.66]0.7620 (<0.001)98.4<0.001∗
      Infection when admitted1.67 [1.19–2.35]0.0000 (0.634)0.00.003∗
      Intravenous infusion2.84 [1.72–4.67]0.0000 (0.761)0.0<0.001∗
      Invasive procedures3.54 [1.50–8.34]1.2942 (<0.001)98.20.004∗
      Length of hospitalization (≥15 days vs <15 days)13.36 [6.80–26.26]0.9830 (<0.001)97.9<0.001∗
      Liver cirrhosis1.28 [1.34–1.45]0.0000 (0.930)0.0<0.001∗
      Long-term bed5.84 [5.12–6.66]0.0075 (0.016)82.8<0.001∗
      Malignant tumour1.95 [1.02–3.73]0.7274 (<0.001)97.50.044∗
      Mechanical ventilation4.59 [2.08–10.16]0.6076 (<0.001)92.8<0.001∗
      Radiotherapy1.50 [0.81–2.78]0.7311 (<0.001)89.60.203
      Surgery1.64 [1.39–1.94]0.2326 (<0.001)93.7<0.001∗
      Tracheal cannula5.35 [3.53–8.11]0.1927 (<0.001)91.2<0.001∗
      Tracheotomy10.44 [7.50–14.53]0.5144 (<0.001)95.9<0.001∗
      Number of underlying diseases (≥3 vs <3)2.63 [1.71–4.06]0.0969 (0.103)51.5<0.001∗
      Use of antibiotics6.64 [3.16–13.96]1.6512 (<0.001)97.3<0.001∗
      Ventilator6.63 [5.41–8.11]0.3229 (<0.001)93.3<0.001∗
      ∗Statistical significance at P<0.05.

      Discussion

      To our best knowledge, our systematic review and meta-analysis was the first to comprehensively assess the risk factors associated with HAIs in Chinese general hospitals at a national level. This review incorporated a total of 1,211,117 hospitalized patients, which were distributed in 41 regions in 23 provinces (34 provincial administrative regions in total) of China. Our systematic review and meta-analysis showed that HAIs in Chinese general hospitals are significantly associated with socio-demographic, invasive procedure, health conditions, healthcare-related risk factors, and longer hospital stays.
      Our review found that patients older than 60 years or male patients were more likely to get HAIs. In line with our findings, Iskender et al. undertook a prospective cross-sectional study in a teaching hospital of Turkey and found the HAIs prevalence was higher among elderly patients (aged over 65 years: 15.1) than those patients aged under 65 years (2.9) [
      • İskender S.
      • Yılmaz G.
      • Köksal İ.
      An examination of healthcare-associated infections in elderly patients.
      ]. Elderly patients are potentially an immune-comprised population. Moreover, elderly patients commonly have other comorbidities, such as cardiovascular disease, cancer, and chronic obstructive pulmonary disease [
      • Zhao X.
      • Wang L.
      • Wei N.
      • Zhang J.
      • Ma W.
      • Zhao H.
      • et al.
      Epidemiological and clinical characteristics of healthcare-associated infection in elderly patients in a large Chinese tertiary hospital: a 3-year surveillance study.
      ], factors which further reduce the immunity of the elderly. A three-year surveillance study on HAIs among elderly patients in a large Chinese tertiary hospital also confirmed that the higher incidence of HAIs in the elderly may be attributable to the higher rates of comorbidities [
      • Zhao X.
      • Wang L.
      • Wei N.
      • Zhang J.
      • Ma W.
      • Zhao H.
      • et al.
      Epidemiological and clinical characteristics of healthcare-associated infection in elderly patients in a large Chinese tertiary hospital: a 3-year surveillance study.
      ]. Elderly patients should be prioritized in the surveillance, prevention and management of HAIs. A cross-sectional study undertaken among elderly hip fracture patients also showed that male patients were more susceptible to obtaining HAIs [
      • Deng Y.
      • Zheng Z.
      • Cheng S.
      • Lin Y.
      • Wang D.
      • Yin P.
      • et al.
      The factors associated with nosocomial infection in elderly hip fracture patients: gender, age, and comorbidity.
      ]. However, this study did not discuss potential mechanisms for the impact of gender on the occurrence of HAIs. Therefore, further study is needed to investigate any differential compliance to the HAIs prevention and control measures or personal behaviour, such as hand washing using alcohol-based rubs or smoking between males and females.
      We also found that patients exposed to invasive procures were more vulnerable to acquiring HAIs. This finding is consistent with those studies conducted in Slovenia [
      • Klavs I.
      • Serdt M.
      • Korošec A.
      • Zupanc T.L.
      • Pečavar B.
      Prevalence of and factors associated with healthcare-associated infections in Slovenian acute care hospitals: results of the third national survey.
      ] and Ethiopia [
      • Alemu A.Y.
      • Endalamaw A.
      • Belay D.M.
      • Mekonen D.K.
      • Birhan B.M.
      • Bayih W.A.
      Healthcare-associated infection and its determinants in Ethiopia: a systematic review and meta-analysis.
      ]. The systematic review and meta-analysis conducted by Rodríguez-Acelas et al. concluded that mechanical ventilation was an independent risk factor associated with an increased HAI rate (OR:12.95 (6.28–26.73)) [
      • Rodríguez-Acelas A.L.
      • de Abreu Almeida M.
      • Engelman B.
      • Cañon-Montañez W.
      Risk factors for health care-associated infection in hospitalized adults: systematic review and meta-analysis.
      ], which is higher than the OR of mechanical ventilation (4.59 (2.08–10.16)) in our review. Moreover, the systematic review and meta-analysis conducted in Ethiopia found that patients who had surgery were more likely to get HAIs (OR: 3.37 (1.85–4.89)) [
      • Alemu A.Y.
      • Endalamaw A.
      • Belay D.M.
      • Mekonen D.K.
      • Birhan B.M.
      • Bayih W.A.
      Healthcare-associated infection and its determinants in Ethiopia: a systematic review and meta-analysis.
      ], which was higher than our OR of surgery in the current review (1.64 (1.39–1.94)). Metsini et al. conducted a point prevalence survey of HAIs in three large Swiss acute-care hospitals and reported that having a medical device, such as peripheral venous catheter, central venous catheter, urinary catheter, endotracheal tube, was an independent risk factor for HAIs (OR: 4.43 (3.49–5.63)) [
      • Metsini A.
      • Vazquez M.
      • Sommerstein R.
      • Marschall J.
      • Voide C.
      • Troillet N.
      • et al.
      Point prevalence of healthcare-associated infections and antibiotic use in three large Swiss acute-care hospitals.
      ], which is similar to the OR of invasive procedures (3.54 (1.50–8.34)) in our review. These findings confirm that invasive procedures are a significant hazard for hospitalized patients for acquiring an HAI. Surgical site infection (SSI) is one of the most common HAIs [
      • Haque M.
      • Sartelli M.
      • McKimm J.
      • Abu Bakar M.
      Health care-associated infections – an overview.
      ]. In order to control the occurrence of HAIs among patients undergoing invasive procedures, it is essential to control the duration of exposure to medical invasive devices, such as arteriovenous cannula, central venous catheter, indwelling urinary catheter, mechanical ventilation, and ventilator. Furthermore, it is vital to comply with disinfection measures to reduce the SSI rate.
      Another finding in our review was that patients with underlying diseases or comorbidities such as diabetes mellitus and liver cirrhosis were at greater risk of HAIs. A systematic review and meta-analysis conducted in Ethiopia also found that underlying non-communicable diseases place patients at greater risk of HAIs (OR: 2.81 (1.39–4.22)) [
      • Alemu A.Y.
      • Endalamaw A.
      • Belay D.M.
      • Mekonen D.K.
      • Birhan B.M.
      • Bayih W.A.
      Healthcare-associated infection and its determinants in Ethiopia: a systematic review and meta-analysis.
      ]. This may be due to underlying diseases weakening the immune system. Two previous studies have described how Type 2 Diabetes and cirrhosis could cause dysfunction of the immune response, therefore failing to prevent the invading pathogens [
      • Berbudi A.
      • Rahmadika N.
      • Tjahjadi A.I.
      • Ruslami R.
      Type 2 Diabetes and its Impact on the Immune System.
      ,
      • Albillos A.
      • Lario M.
      • Alvarez-Mon M.
      Cirrhosis-associated immune dysfunction: distinctive features and clinical relevance.
      ]. Long-term bed stays were also found to be a significant risk factor associated with HAIs, though this has not been well studied in current literature, and it also indicated that the sample size was not sufficient in our review. There is a need to collect empirical data to explore the underlying mechanism, and make corresponding prevention and control measures to reduce the HAIs rate among these patients.
      Healthcare-related risk factors including chemotherapy, haemodialysis, hormone therapy, and use of antibiotics were also found to significantly increase the risk of acquiring HAIs for patients in our review. However, the effects of chemotherapy, haemodialysis, and hormone therapy are not well investigated in existing literature, and further empirical data are needed. Some studies have found that use of antibiotics is related to an increased HAIs rate, such as the long-time use of antibiotics [
      • Hanley S.
      • Odeniyi F.
      • Feemster K.
      • Coffin S.E.
      • Sammons J.S.
      Epidemiology and risk factors for healthcare-associated viral infections in children.
      ], the excessive volume of antibiotics use, and prophylactic antimicrobial therapy [
      • Barbato D.
      • Castellani F.
      • Angelozzi A.
      • Isonne C.
      • Baccolini V.
      • Migliara G.
      • et al.
      Prevalence survey of healthcare-associated infections in a large teaching hospital.
      ]. These studies highlight the irrational use of antibiotics, which ultimately results in antimicrobial resistance (AMR), a well-known global health issue. Therefore, antimicrobial stewardship programmes or campaigns are pivotal to make appropriate use of antibiotics. It is also essential to control and monitor the health professionals' prescription behaviour to prevent irrational use of antibiotics. Likewise, the public's knowledge, attitudes, and practices relating to the use of antibiotics are also important. It is necessary to increase the awareness of the public and health professionals to achieve the goal of prudent high-quality antibiotics use.
      Hospitalization stays longer than 15 days were recognized as a significant risk factor associated with the increased occurrence of HAIs in our review and has been well investigated in current literature [
      • Liu X.L.
      • Ren N.L.
      • Ma Z.F.
      • Zhong M.L.
      • Li H.
      Risk factors on healthcare-associated infections among tuberculosis hospitalized patients in China from 2001 to 2020: a systematic review and meta-analysis.
      ,
      • Murni I.K.
      • Duke T.
      • Kinney S.
      • Daley A.J.
      • Wirawan M.T.
      • Soenarto Y.
      Risk factors for healthcare-associated infection among children in a low-and middle-income country.
      ]. It is possible for hospitalized patients to be predisposed to HAIs for prolonged hospitalization. Consequently, patients are more susceptible to HAIs. Therefore, it is important to place patients with long hospitalization under surveillance, especially those patients with extremely long hospitalization, and prioritize safely shortening hospitalization stays.
      There are likely interactions between the risk factors associated with HAIs in our review. For example, elderly patients, underlying diseases or comorbidities, and therapy of immunosuppression were the three significant risk factors associated with HAIs according to our meta-analyses. Elderly patients require long-term care and immunosuppressive therapy, and they are more likely to have underlying disease or comorbidities [
      • İskender S.
      • Yılmaz G.
      • Köksal İ.
      An examination of healthcare-associated infections in elderly patients.
      ,
      • Zhao X.
      • Wang L.
      • Wei N.
      • Zhang J.
      • Ma W.
      • Zhao H.
      • et al.
      Epidemiological and clinical characteristics of healthcare-associated infection in elderly patients in a large Chinese tertiary hospital: a 3-year surveillance study.
      ]. Therefore, comprehensive prevention and control measures need to be taken according to the evidence-based risk factors to reduce the burden attributable to HAIs.
      Our systematic review and meta-analysis has some limitations. First, the included studies were mostly published in Chinese journals, which constrain the large scale of researchers from other countries in sharing the knowledge. Second, we also found that most of the included studies were single-centre studies. Multi-centre studies are needed to provide more robust findings. Third, our review shows that the publication bias among the included studies for all the potential risk factors existed, and the unadjusted ORs were calculated. Therefore, the relationships between the potential risk factors and HAIs might be overstated. It is better to estimate the adjusted ORs by controlling the potential confounders.
      In conclusion, age older than 60 years and male sex, invasive procedure including arteriovenous cannula, deep vein catheterization, drainage, indwelling central catheter, indwelling urinary catheter, intravenous infusion, mechanical ventilation, surgery, tracheal cannula, tracheotomy and ventilator, health conditions as chronic diseases, coma, diabetes mellitus and long-term bed stay, healthcare-related risk factors including chemotherapy, haemodialysis, hormone therapy, immunosuppression, more than three underlying diseases and use of antibiotics, and longer than 15 hospitalization days were established as the main risk factors among hospitalized patients with HAIs compared with those without HAIs in Chinese general hospitals. Our review could help health professionals and service managers to make corresponding prevention and control measures to reduce the occurrence of HAIs. It is necessary to conduct further empirical research to confirm some risk factors for HAIs which are not well documented in current literature.

      Author contributions

      X.L. drafted and revised the systematic review and conducted the meta-analyses. X.L. and Y.L. searched the targeted databases to find the relevant articles and assessed the quality of the included studies. A.S., A.V., C.G., and S.S. commented on the systematic review. J.W. recommended the methodology of the systematic review. H.L. commented on the discussion of the systematic review. X.L. and A.S. designed the systematic review framework. A.S. and C.G. proofread the whole systematic review.

      Conflict of interest statement

      The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

      Funding sources

      This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

      Appendix A. Supplementary data

      The following is the Supplementary data to this article:

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