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Prevalence and associated factors of needle stick and sharps injuries among healthcare workers in northwestern Ethiopia

  • Zemene Berhan ,

    Contributed equally to this work with: Zemene Berhan, Metadel Adane

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Quality Improvement Unit, Finote Selam General Hospital, Finote Selam, Ethiopia

  • Asmamaw Malede,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Adinew Gizeyatu,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Tadesse Sisay,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Mistir Lingerew,

    Roles Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Helmut Kloos,

    Roles Resources, Supervision, Validation, Visualization, Writing – review & editing

    Affiliation Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America

  • Mengesha Dagne,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Mesfin Gebrehiwot,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Gebremariam Ketema,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Pharmacy, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Kassahun Bogale,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Pharmacy, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Betelhiem Eneyew,

    Roles Investigation, Methodology, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Seada Hassen,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Tarikuwa Natnael,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Mohammed Yenuss,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Leykun Berhanu,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Masresha Abebe,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Gete Berihun,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Birhanu Wagaye,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Public Health Nutrition, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Kebede Faris,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Awoke Keleb,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Ayechew Ademas,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Akalu Melketsadik Woldeyohanes,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Alelgne Feleke,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Tilaye Matebe Yayeh,

    Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Statistics, College of Natural Sciences, Wollo University, Dessie, Ethiopia

  • Muluken Genetu Chanie,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Health Systems and Policy, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Amare Muche,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Reta Dewau,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Zinabu Fentaw,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Wolde Melese Ayele,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Wondwosen Mebratu,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Bezawit Adane,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Tesfaye Birhane Tegegne,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Elsabeth Addisu,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Mastewal Arefaynie,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Melaku Yalew,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Yitayish Damtie,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Bereket Kefale,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Zinet Abegaz Asfaw,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Reproductive and Family Health, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Atsedemariam Andualem,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Nursing, School of Nursing and Midwifery, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Belachew Tegegne,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Nursing, School of Nursing and Midwifery, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

  • Emaway Belay,

    Roles Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization

    Affiliation Department of Public Health, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia

  •  [ ... ],
  • Metadel Adane

    Contributed equally to this work with: Zemene Berhan, Metadel Adane

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    metadel.adane2@gmail.com

    Affiliation Department of Environmental Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia

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Abstract

Background

Needle stick and sharp injuries (NSSIs) are a common problem among healthcare workers (HCWs). Although the factors related to NSSIs for HCWs are well documented by several studies in Ethiopia, no evidence has been reported about the magnitude of and factors related to NSSIs in hospitals in northwestern Ethiopia.

Methods

An institution-based cross-sectional study was carried out from January to March 2019 among 318 HCWs in three randomly-selected hospitals of the eight hospitals found in South Gondar Zone. Sample sizes were proportionally allocated to professional categories. Study participants were selected by systematic random sampling methods using the monthly salary payroll for each profession as the sampling frame. Data were collected using a self-administered questionnaire. The outcome of this study was the presence (injured) or absence of NSSIs during the 12 months prior to data collection. A binary logistic regression model with 95% confidence interval (CI) was used for data analysis. Variables from the bi-variable analysis with a p-value ≤ 0.25 were retained into the multivariable analysis. From the multivariable analysis, variables with a p-value less than 0.05 was declared as factors significantly associated with NSSIs.

Main findings

The prevalence of NSSIs was 29.5% (95% CI: 24.2–35.5%) during the 12 months prior to the survey. Of these, 46.0% reported that their injuries were moderate, superficial (33.3%) or severe (20.7%). About 41.4% of the injuries were caused by a suture needle. Factors significantly associated with NSSIs were occupation as a nurse (adjusted odds ratio [AOR] = 2.65, 95% CI: 1.18–4.26), disposal of sharp materials in places other than in safety boxes (AOR = 3.93, 95% CI: 2.10–5.35), recapping of needles (AOR = 2.27, 95% CI: 1.13–4.56), and feeling sleepy at work (AOR = 2.24, 95% CI: 1.14–4.41).

Conclusion

This study showed that almost one-third of HCWs had sustained NSSIs, a proportion that is high. Factors significantly associated with NSSIs were occupation as a nurse, habit of needle recapping, disposal of sharp materials in places other than in safety boxes and feeling sleepy at work. Observing proper and regular universal precautions for nurses during daily clinical activities and providing safety boxes for the disposal of sharp materials, practicing mechanical needle recapping and preventing sleepiness by reducing work overload among HCWs may reduce the incidence of NSSIs.

Background

Healthcare workers (HCWs) are at risk of acquiring life-threatening blood-borne infections through needle stick and sharps injuries (NSSI) in their work place [1]. NSSIs occur during screening, diagnosing, treating, and monitoring patients, and disposal of needles and other sharp materials. HCWs who sustain NSSIs experience psychiatric morbidity such as depression, post-traumatic stress disorder, and adjustment disorder. The consequences of these effects include absenteeism and poor healthcare service delivery [2].

Globally, 86% of occupationally related infections are reportedly due to needle stick injuries [3] and the disease burden caused by percutaneous sharps injuries is approximately 3 million infections per year [2]. The burden of needle sticks and other percutaneous injuries among HCWs in Germany and UK were reported to be 500,000 and 100,000 per year, respectively [4]. HCWs are at risk of acquiring hepatitis B virus (HBV), hepatitis C virus (HCV) and HIV infections by sharps injuries [2, 4, 5]. About 40% of all HBV, 40% of HCV, and 4.4% of HIV/AIDS cases among HCWs are due to NSSIs [2].

In sub-Saharan Africa, many NSSIs are due to overwork and inadequate personal protective equipment (PPE), resulting in multiple injuries per HCW each year [6]. One study revealed that the prevalence of NSSIs among HCWs in sub-Saharan Africa was 32.0% in 2013 [7]. NSSIs have several routes of exposure: for instance in northern Uganda, 5.1% of HIV exposure was associated with sharp objects [8], and 57% of the nurses and midwives had experienced at least one needle stick injury per year [9]. A study in Kenya’s Rift Valley Provincial Hospital reported that 19% of health care workers reported having sustained percutaneous injuries, 7.2% splashes to mucosal membranes, and 25% exposure to blood and other body fluids in the past 12 months. High rates of percutaneous injuries were reported by nurses (50%) during stitching (30%) and in the obstetric and gynecologic department (22%) [10].

In Ethiopia, studies conducted in Addis Ababa and Bale Zone reveal that 66.6% and 39.3% of HCWs had sustained NSSI, respectively [11, 12]. The Federal Ministry of Health of Ethiopia developed guidelines for infection prevention and post-exposure prophylaxis use in 2004, 2005 and 2015 [13]. Their aim was to prevent NSSIs among HCWs through ensuring clean and safe health facilities.

Needle-stick incidents are associated with a number of different work activities, including heavy workload, working in surgical or intensive care units, insufficient work experience, and young age [14]. Although data on the prevalence of NSSIs and associated factors among HCWs exist in many larger urban health facilities in Ethiopia [12, 1519], these study findings are not comparable due to variations in healthcare delivery, occupations of HCWs, methods of injection, drawing of blood and needle disposal, and the practice of recapping needles [20, 21]. Moreover, no study has been conducted in South Gondar Zone hospitals in northwestern Ethiopia to identify the prevalence of NSSI and associated factors among the area’s HCWs, which hinders appropriate actions to prevent them. This study was designed to provide such local evidence.

Methods

Study setting

This study was conducted in South Gondar Zone hospitals in northwestern Ethiopia. South Gondar Zone, one of the 13 zones in Amhara Region, is divided into 18 districts. Its capital city is Debre Tabor, which is about 600 km north of Addis Ababa and about 110 km east of Bahir Bahir Dar. The study included one general government hospital (Debre Tabor general hospital) and two of the seven district hospitals in South Gondar Zone, Amhara National Regional State.

Debre Tabor general hospital is found in Debre Tabor Town and the seven district primary government hospitals are in Addis Zemen, Mekane Eyesus, Andabet, Ebnat, Nefas Mewcha, Arb Gebeya, and Smada towns. In addition, there are 98 government health centers and 76 private clinics in South Gondar Zone [22]. After this study conducted, Debre Tabor general hospital was promoted to Debre Tabor Comprehensive Specialized Hospital and Tach Gayint Primary Hospital was renamed by Dr. Ambachew Mekonen Memorial Primary Hospital. Hereafter, we used the new names for consistency with the future studies.

Study design and source population

An institution-based cross-sectional study was conducted from January to March 2019. The source population of this study consisted of all HCWs working in eight South Gondar Zone government hospitals. The study populations were HCWs working in the three randomly selected hospitals for this study.

Inclusion and exclusion criteria

The HCWs participating in this study included nurses, midwives, laboratory technicians, health officers, medical doctors (general practitioners, gynecologists/obstetricians, anesthesiologists, internists, pediatricians, surgeons, and ophthalmologists), dentists, cleaners and laundry staff. However, pharmacists and environmental health professionals were excluded in this study because they are less vulnerable for NSSIs.

Sample size determination and sampling procedures

Sample size was determined using a single population proportion () formula [23] with an assumption of Zα/2 at 95% confidence interval is 1.96; d is degree of error of 5%; and proportion (p) of NSSIs among HCWs of 32.8% was taken from a study done in Debre Birhan hospitals in Amhara Region [19]. We used a design effect of 1.5 since we employed a multi-stage sampling method, giving a calculated sample size of 508. Furthermore, since the source population in South Gondar Zone hospitals was less than 10,000, we used a sample size correction formula of n/[1+ (n-1)/N] [23], where n is the initial calculated sample size (508) and N is the source population (749). Then, the sample size became 303. Finally, a 5% non-response rate was added and a final sample size of 318 was obtained.

A two-stage sampling method was employed. During the first stage, Debre Tabor Comprehensive Specialized hospital, and Mekane Eyesus and Dr. Ambachew Mekonen Memorial Primary Hospitals were selected using the lottery method from the eight hospitals found in South Gondar. A total of 442 HCWs worked in the three hospitals, 320 of them in Debre Tabor Comprehensive Specialized Hospital, 71 in Mekane Eyesus Primary Hospital and 51 in Dr. Ambachew Mekonen Memorial Primary Hospital. Based on the number of HCWs in each hospital, the sample size for this study was proportionally allocated to the three selected hospitals. Similarly, the sample size of each category of profession (nurses, medical doctors, laboratory technicians, health officers, cleaners and laundry workers) was proportionally allocated.

At the second stage, the participating HCWs were selected by using the monthly salary payroll as the sampling frame. Thus, a separate sampling frame was prepared for each profession based on the monthly salary payroll. Then, the study participants in each profession who adhered to the inclusion criteria were selected using a systematic random sampling technique.

Operational definitions

Healthcare Workers (HCWs).

In this study, HCWs were nurses, midwives, laboratory technicians, health officers, general practitioners, gynecologists/obstetricians, anesthesiologists, internists, pediatricians, surgeons, and ophthalmologists, dentists, cleaners and laundry staff whose activities involved contact with needles and other sharps during the course of their work in a healthcare facility [2].

Medical sharps.

Any object used in the healthcare setting that can penetrate the skin, including suture needles, hypodermic needles, disposable needles, blood sugar lances, surgical scalpels, trocar puncture needles, vacuum tube blood collection needles, broken vials or ampules, razors, scissors, scalpels, lancets, retractors, broken capillary tubes, and glassware [2].

Needle Stick and Sharps Injury (NSSI).

The outcome variable of this study is the presence or absence of NSSI during the 12 months prior to data collection. The presence of NSSIs was measured by self-reporting the penetration of the skin by needles or other sharp objects that had been in contact with blood, tissue, or a body fluid before the exposure [2].

Needle Stick and Sharps Injury (NSSI) types.

NSSI can be classified as moderate, severe and superficial. The moderate category includes puncturing of the skin involving some bleeding; severe NSSIs include deep sticks/cut or profuse bleeding and the superficial group injuries caused by sharps that resulted in little or no bleeding [24].

Prevalence of NSSI.

The ratio of the number of HCWs who sustained NSSIs to the total number of HCWs during the 12 months prior to data collection multiplied by 100.

Personal Protective Equipment (PPE).

Equipment designed to protect workers from workplace injuries or illnesses resulting from contact with blood, body fluid, and radiological, physical, mechanical, or other workplace hazards. This includes a variety of devices and garments, such as masks, gloves and eye goggles [25].

Recapping.

The act of replacing a protective sheath on a needle [26].

Universal precautions.

The practice of standard set of guidelines by healthcare workers to avoid contact with patients’ bodily fluids for the prevention of the transmission of blood-borne pathogens [27].

Data collection tools, data collection and quality assurance

Data were collected using a structured, self-administered questionnaire. The questionnaire was prepared after reviewing similar studies on NSSIs [11, 28]. The questionnaire was first prepared in English, then translated to Amharic (local language), and then retranslated back to English to check for consistency. The instrument elicited information on socio-demographic characteristics of respondents and organization-related, skill-related, and behavior-related factors. Three data collectors with BSc degrees in nursing were recruited from Debre Tabor Town and were trained for one day on the study instrument and data collection procedures. Then, one data collector was assigned to each hospital to collect data using a self-administered questionnaire from the participating HCWs who had contact with sharps and needle instruments during the course of their work in the 12-month recall period preceding the survey.

Data quality was assured during questionnaire design and data collection, entry, and analysis. The questions were objective, non-leading, logically sequenced, and free of scientific jargon. To ensure the validity of the data collection tool, inter-observer reliability was ensured by providing clear definitions of measured variables, and events to be recorded. We re-self-administered 5% of the study participants to check reliability of the information entered at different times about the same study participant. Furthermore, to ensure the content of the survey tool was valid, the questionnaire was pretested in a 10% sample of the study’s sample of HCWs in nearby hospital (Lay Gayint Hospital). Based on the pre-test responses, questions were revised as necessary.

The principal investigator provided one day’s training to data collectors, and then reviewed the collected data each day, returning incomplete questionnaires to data collectors who in turn contacted the study participants the same day. In order to reduce social desirability bias in answers, a self-administered survey and closed-ended questions were used. In order to verify the accuracy of data entries, two generic data verification strategies were employed as described in another study [29]. As the first step, randomly selected 10% of the questionnaires were thoroughly checked. Following this, descriptive statistics, results from cross-tabulations, and frequency distributions were examined before performing statistical analysis.

Data management and analysis

The collected data were entered into EpiData version 3.1 (EpiData Association, Odense, Denmark) and exported to Statistical Package for the Social Sciences (SPSS) version 24.0 software (IBM Corp., Armonk, N.Y., USA) for data cleaning and analysis. Descriptive statistics such as frequencies and percentages were calculated to examine the overall distribution of the variables. Multicollinearity was checked using standard error of the coefficient with a cut-off point of 2 [30].

A binary logistic regression model was used to examine the association between independent variables and NSSI. Independent variables having p-value ≤ 0.25 from the bi-variable analysis were retained into multivariable analysis. Then, in the multivariable analysis, p-value < 0.05 and AOR (adjusted odds ratio) with 95% CI were used to measure associations; variables with p-value < 0.05 were declared as statistically significant and associated factors of NSSI. Model fitness was checked using the Hosmer and Lemeshow test [30] to conduct logistic regression analysis when the model is fit at p-value > 0.05.

Ethical consideration

This study adhered to the ethical principles of the Declaration of Helsinki [31] and the principles that govern medical research involving human subjects [32]. Thus, ethical clearance was obtained from the Ethical Review Committee of Wollo University, College of Medicine and Health Sciences. The study participants were informed of the purpose of the study before asking for their written consent for participation. The respondents’ right to refuse or withdraw from participation in the study was fully maintained and the information provided by each respondent was kept confidential through the use of codes rather than names. Study participants who were with NSSI during data collection and who had not recovered from their injuries were advised to get treatment.

Results

Socio-demographic characteristics of healthcare workers

Of the 318 HCWs selected for study, 295 (92.8%) participated. They included 124 (42.0%) nurses, 25 (8.5%) midwives, 21 (7.1%) laboratory technicians, 26 (8.8%) medical doctors (general practitioners), 52 (17.6%) cleaners and laundry workers and 45 (15.3%) other healthcare professionals. Nearly half 140 (47.5%) of the respondents were between 25–30 years old, 148 (50.2%) were females and 181 (61.4%) were unmarried. Seven out of 10 (69.8%) HCWs had less than five years of work experience (Table 1).

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Table 1. Socio-demographic characteristics and bi-variable analysis with NSSIs among healthcare workers in South Gondar Zone hospitals, January to March 2019.

https://doi.org/10.1371/journal.pone.0252039.t001

Organization-related characteristics

About 295 HCWs (n = 259, 87.8%) reported working 8 or fewer hours per day. More than two-thirds (68.1%) did not work night shifts. One hundred eighty-five (62.7%) HCWs knew that a safety protocol was in place, but most (71.9%) did not know that universal precautions posters were posted in their institutions. About 61.4% of the respondents disposed of needles and other sharp materials in safety boxes and 178 (60.3%) had boxes for sharps in their work rooms (Table 2).

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Table 2. Organization-related characteristics and bi-variable analysis with NSSIs among healthcare workers in South Gondar Zone hospitals, January to March 2019.

https://doi.org/10.1371/journal.pone.0252039.t002

Behavioral characteristics

Almost half 143 (48.5%) of the HCWs reported that they habitually recapped needles, 72 (24.4%) reported feeling sleepy at work, 53 (18.0%) drank alcohol, 8 (2.7%) chewed chat (Catha edulis), and 14 (4.7%) smoked cigarettes occasionally. Two hundred-seventy (91.5%) of the HCWs knew about the risk of disease transmission through NSSIs (Table 3).

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Table 3. Behavioral characteristics and bi-variable analysis with NSSIs among healthcare workers in South Gondar Zone hospitals, January to March 2019.

https://doi.org/10.1371/journal.pone.0252039.t003

Skill-related characteristics

Nearly three-quarters (n = 213, 72.2%) of the HCWs were not trained about infection prevention and 208 (70.5%) received no training about patient safety and injection safety. About 259 (87.8%) had no access to information about NSSIs and 277 (93.9%) had no knowledge of how to prevent NSSIs (Table 4).

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Table 4. Skill-related characteristics and bi-variable analysis with NSSIs among healthcare workers in South Gondar Zone hospitals, January to March 2019.

https://doi.org/10.1371/journal.pone.0252039.t004

Prevalence of Needle Stick and Sharps Injuries (NSSIs)

The overall prevalence of NSSIs among HCWs was 29.5% with a 95% CI (24.2–35.5%) during the 12 months prior to the survey. Among the 87 injured respondents, 40 (46.0%) reported that their injuries were moderate, 29 (33.3%) reported superficial injuries, and 18 (20.7%) reported severe injuries. Sixty-eight (78.2%) had sustained injuries only one time in the previous 12 months and 8.0% recalled three or more injuries. Thirty-six (41.4%) of the injuries were caused by suture needles and 27.6% by disposable syringes (Table 5).

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Table 5. Prevalence of NSSIs and characteristics of injured healthcare workers in South Gondar Zone hospitals, January to March 2019.

https://doi.org/10.1371/journal.pone.0252039.t005

Factors associated with needle stick and sharps injuries

In the bi-variable logistic regression analyses of the variables presented in Tables 14, the following were candidates for multivariable regression with p-value ≤ 0.25: occupation, level of education, monthly income, IPPS training, disposal method of sharp material, HBV vaccination status, habit of needle recapping, feeling sleepy at work, alcohol use, chat use, cigarette use, and injection safety training. After controlling the confounding factors, the following variables were found to be significantly associated with NSSIs (P-value < 0.05): occupation, disposal of sharp materials, habit of needle recapping, and feeling sleepy at work.

The analysis shows that the odds of nurses being injured by NSSIs were 2.65 times (AOR = 2.65, 95% CI: 1.18–4.26) higher than for midwives. This study also indicated that HCWs who disposed of sharp materials without safety boxes were 3.93 times (AOR = 3.93, 95% CI: 2.10–5.35) more likely to have NSSIs than those who disposed them in safety boxes. Those workers who reported feeling sleepy at work were 2.24 times (AOR = 2.24, 95% CI: 1.14–4.41) more likely to sustain NSSIs than those who did not feel sleepy at work. Health workers who recapped needles were 2.27 times (AOR = 2.27, 95% CI: 1.13–4.56) more likely to be injured by them than those who did not report this practice (Table 6).

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Table 6. Factors associated with NSSIs among healthcare workers from multivariable logistic regression analysis in South Gondar Zone hospitals, January to March 2019.

https://doi.org/10.1371/journal.pone.0252039.t006

Discussion

This institution-based cross-sectional study was designed to assess the prevalence of NSSIs and associated factors among HCWs in hospitals of northwestern Ethiopia. We found that the prevalence of NSSIs was 29.5% during the 12 months prior to the survey. Factors significantly associated with NSSIs were occupation (being a nurse), method of disposal of sharp materials, the practices of needle recapping and feeling sleepy at work.

The prevalence of NSSIs in this study was similar to studies conducted in Tigray Region health facilities (25.9%) [33], and in a Tamil Nadu, India, which reported a one-year prevalence of NSSI of 35.3% among HCWs [1]; in Goa Territory Hospital in India, which reported a 34.8% prevalence [34]; and in sub-Saharan Africa, the average prevalence of NSSI among HCWs to be 32% [7]. In Ethiopia, NSSIs were reported in 26.6% of HCWs in Dire Dawa Town [15] and 32.8% in Debre Berhan Town [19]. In a hospital in Bahir Dar Town, 31.0% of HCWs sustained a NSSI at least once during a 12-month period [18]. These similar rates may be due to the fact that all these facilities are mid-level regional or district hospitals with similar levels of staff training and national IPPS guidelines have been implemented in each hospital.

The prevalence of NSSIs in our study was higher than in studies conducted in Assam, India; Lausanne, Switzerland; and Awi and East Gojjam zones in Ethiopia, where the proportions of injuries during 12-month periods were 21.1%, 9.7%, 18.7% and 22.2%, respectively [24, 3537]. The possible reasons for these differences might be the lack of adequate sharps disposal sites such as safety boxes and lower adherence to standard precautions. Other reasons might be inadequate training and fewer safety guidelines for the prevention of injuries during patient care in our study hospitals.

The prevalence of NSSIs in our study was also lower than reported by studies conducted in different parts of Ethiopia: 37.1% in Bale Zone hospitals [38]; 39.3% in Jimma Zone hospitals [14]; 35.8% in Hawassa healthcare facilities [16] and 42.8% in Bahir Dar health centers [17]. The difference between the prevalence in our study and those in the other Ethiopian studies may be due to differences in working environments. Furthermore, the functionality of existing IPPS committee, variation in prevention posters displayed in different wards or in the health facility compound and the lack of sufficient safety boxes may have influenced the outcome of these various studies.

The odds of having NSSIs were 2.65 times higher among nurses than among midwives. Consistent with our findings, being a nurse in Poland is also a factor in NSSIs [39]. Several studies also reported high incidence of NSSIs among nurses in Iran [40], in the University of Alexandria teaching hospitals (92.5%) [21], among hospital nurses in South Korea (70.4%) [41], nurses in India (71%) [42] and in Poland (72.6%). This may be because of the high work load of nurses and the high risk of exposure during drug administration and other procedures that require the use of needles and other sharp instruments.

HCWs who disposed of sharp materials without using safety boxes were 3.93 times more likely to sustain NSSIs than those who used safety boxes. Similarly, a study done in London indicated that most NSSIs were caused by disposal of sharp materials without using safety boxes [43]. In a hospital in Iran, the appropriate disposal of used needles nearly eliminated the risk of NSSIs [44]. This discussion indicates that lack of safety boxes, inappropriate and uncontrolled disposal of sharps, and lack of awareness of the risk involved in handling sharps might be largely responsible for NSSI. About 8.1% of NSSI happened while walking in the hospital. This might be due to walking to visit the toilet, during moving from one ward to another, during moving from one location to another during tea break time. This also might have been as a result of lack of cleaning away of sharp materials from the hospital compound. In addition to this, lack of monitoring of the standard infection prevention and control strategies may bring about this horrible situation.

The odds of NSSIs among HCWs who habitually recapped needles were 2.27 higher than for those who did not recap needles. This is consistent with findings from other Ethiopian studies in in Tigray Region, Hawassa, Addis Ababa, Ethiopia [14, 33, 45], Bahir Dar City [18] Jimma Zone, which showed that 37.3% of NSSIs were due to needle recapping, and also in Bale Zone, where HCWs who practiced needle recapping had a 46% higher risk of NSSI [46].

Furthermore, our findings are also consistent with other country studies; a study conducted in Shiraz, Iran, identified recapping as the major cause of NSSIs [47] and a study in hospitals of Pokhara, Nepal, found recapping to account for 55.1% of NSSIs [48]. A study in a tertiary care hospital in India reported that 63.7% of NSSIs occurred during recapping of needles [49]. In a tertiary care hospital in Assam, recapping was associated with 26.3% of all NSSIs [50].

Workers who reported feeling sleepy at work were 2.24 times more likely to be injured by needles and other sharps than those whose sleep was not disturbed. Feeling sleepy at work may be linked with tiredness and increased vulnerability to NSSIs of HCWs working night shifts. This can be prevented by minimizing clinical activities and adding more HCWs at this time. This finding is consistent with results of a study conducted in East Gojjam Zone [37]. Feeling sleepy at work may also result from stressful psychosocial working conditions [51].

This study had several limitations. The 12-month recall period may have led to under-reporting of the prevalence of NSSIs and the circumstances under which they occurred. Moreover, the cross-sectional study design could not establish cause-and-effect relationships due to the retrospective nature of questions on exposure risk. Furthermore, it is difficult to measure feeling sleepy at work by closed-ended yes/no questions due to social desirability bias. We also did not measure the level of substance and alcohol use.

Implication of the study for practice

This study will have implications for futher strengthening infection prevention and patient safety programs in hospitals to control injuries among healthcare workers. Furthermore, this study will help to prevent diseases due to injuries, including HIV/AIDS and HBV. Controlling injuries at hospitals will also help to ensure healthy workers and thus facilitate the delivery of healthcare services. The findings can guide programmers and managers of hospitals and other stakeholders (government and non-governemntal organziations) to design a mechanism to minimize NSSI and ensure adequate hospital staffing, provision of IPPS training and of necessary safety equipment. The findings may therefore strengthen the promotion and implementation of IPPS programs in hospitals.

Conclusions

We conclude that almost one-third of the study participants had sustained NSSIs at least once in the previous 12 months. Occupation as a nurse, the habit of needle recapping, feeling sleepy at work and disposing of sharp materials in places other than safety boxes were found to be factors associated with NSSI. To minimize NSSIs, adequate hospital staff recruitment, provision of IPPS training, and provision of necessary safety equipment are recommended. We also recommend promoting and strengthening the implementation of IPPS and strengthening safe hospital committees. This should include provision of safety boxes, mechanical needle recapping devices, health education, and on-the-job training. Health education should emphasize regular use of universal precautions during HCWs’ daily activities and dealing with sleepiness at work among HCWs working night and day shifts. We recommend that HCWs working combined day and night shifts work only day or night shifts to prevent sleepiness. Qualitative studies should be triangulated to investigate further factors in NSSIs. Furthermore, a cohort study design incorporating the use of diaries by healthcare workers is recommended to investigate causal relationships and reduce recall bias.

Acknowledgments

We acknowledged administrators of Debre Tabor Comprehensive Specialized Hospital, Mekane Eyesus and Dr. Ambachew Mekonen Memorial Primary hospitals for their support and permission to conduct this study. The study participant HCWs are also acknowledged for providing relevant information and the data collectors for their assistance. We also thank Lisa Penttila for language editing of the manuscript.

References

  1. 1. Lakshmi A, Raja A, Paul CM. A cross sectional study on needle stick and sharp injuries among health care providers in tertiary centers, Tamil Nadu. Int J Community Med Public Health. 2018;5(3):982–6.
  2. 2. WHO. Reducing risk, promoting health life. Geneva: WHO. Geneva. 2005.
  3. 3. Rezaeian M, Asadpour M, Khademrezaeian H. Epidemiology of occupational exposure to needlestick and body fuids among doctors and medical students in Rafsanjan University of Medical Sciences. J Occup Health Epidemiol. 2012;1(1):44–9.
  4. 4. Rampal L, Zakaria R, Sook LW, Zain AM. Needle stick and sharps injuries and factors associated among health care workers in a Malaysian hospital. Eur J Soc Sci. 2010;13(3):354–62.
  5. 5. Newsletter African. Occupational Health and Safety 2010;20:20–2.
  6. 6. McCoy D, Bennett S, Witter S, Pond B, Baker B, Gow J, et al. Salaries and incomes of health workers in sub-Saharan Africa. The Lancet. 2008;371(9613):675–81. pmid:18295025
  7. 7. Gholami A, Borji A, Lotfabadi P, Asghari A. Risk factors of needlestick and sharps injuries among healthcare workers. Int J Hosp Res. 2013;2(1):31–8.
  8. 8. Odongkara B, Mulongo G, Mwetwale C, Akasiima A, Muchunguzi H, Mukasa S, et al. Prevalence of occupational exposure to HIV among health workers in Northern Uganda. Int J Risk Saf Med. 2012;24(2):103–13. pmid:22751192
  9. 9. Nsubuga FM, Jaakkola MS. Needle stick injuries among nurses in sub‐Saharan Africa. Trop Med Int Health. 2005;10(8):773–81. pmid:16045464
  10. 10. Mbaisi EM, Wanzala P, Omolo J. Prevalence and factors associated with percutaneous injuries and splash exposures among health-care workers in a provincial hospital, Kenya, 2010. Pan Afr Med J. 2013;14(1).
  11. 11. Feleke BE. Prevalence and determinant factors for sharp injuries among Addis Ababa hospitals health professionals. Sci J Public Health. 2015;1(5).
  12. 12. Bidira K, Woldie M, Nemera G. Prevalence and predictors of needlestick injury among nurses in public hospitals of Jimma Zone, South West Ethiopia. Int J Nurs Midwifery. 2014;6(7):90–6.
  13. 13. Federal Minsitry of Health. Infection prevention and patient safety (IPPS) national gudeline. Addis Ababa, Ethiopia 2015.
  14. 14. Feleke BE. Prevalence and determinant factors for sharp injuries among Addis Ababa hospitals health professionals. Sci J Public Health. 2013;1(5):189–93.
  15. 15. Mekonnen R, Henok Yosef H, Teklegiorgis K, Tesfaye F, Dagne I. Magnitude and impact of occupational related sharp and needle stick injuries and associated factors among healthcare workers in Dire Dawa, Eastern Ethiopia. Med Saf Glob Health. 2018;7:2–7.
  16. 16. Hunachew B, Biruk D. Occupational risk factors associated with needle-stick injury. Occup Med Health Aff. 2014;2(156).
  17. 17. Legesse W, Anemaw W, Mekonen T, Nigus D. Prevalence of needle sticks injury and its associated factors among health care workers in Bahir Dar city health centers, Northwest Ethiopia. Int J Infect Dis. 2015;11(2).
  18. 18. Walle L, Abebe E, Tsegaye M, Franco H, Birhanu D, Azage M. Factors associated with needle stick and sharp injuries among healthcare workers in Felege Hiwot Referral Hospital, Bahir Dar, Northwest Ethiopia: Facility based cross-sectional survey. Int J Infect Control. 2013;9(4):1–9.
  19. 19. Sharew NT, Mulu GB, Habtewold TD, Gizachew KD. Occupational exposure to sharps injury among healthcare providers in Ethiopia regional hospitals. Ann Occup Environ Med. 2017;29(7). pmid:28344815
  20. 20. Kurt V, Donovan M, Tazhmoye C, Ruby L, Alexander L, Rachael I. Prevalence of injuries and R = reporting of accidents among healthcare workers at the University Hospital of the West Indies, Jamaica Int J Occup Med Environ Health. 2010;23(2):133–43. pmid:20630834
  21. 21. Hanafi M, Mohamed A, Kassem M, Shawki M. Needlestick injuries among health care workers of University of Alexandria Hospitals. East Mediterr Health J. 2011; 17 (1):26–35. pmid:21735798
  22. 22. SGHB. South Gondar Health Burea 2019 second quarter report. Debre Tabor, Amhara Region, Ethiopia. 2019.
  23. 23. Kelsey JL, Whittemore AS, Evans AS, Thompson WD. Methods in observational epidemiology: Monographs in Epidemiology and Biostatistics. New York, Oxford: Oxford University Press; 1996.
  24. 24. Dilie A, Amare D, Gualu T. Occupational exposure to needle stick and sharp injuries and associated factors among health care workers in Awi Zone, Amhara Regional State, Northwest Ethiopia, 2016. J Environ Public Health. 2017;2017(2438713):1–6.
  25. 25. Rose GK, Sunley. Sharps safety in health care regulation; Royal College of Nursing, 1–23. 2013.
  26. 26. OSHA. Needlestick prevention guidline. American Nurses Associstion, 1–63. 2006.
  27. 27. Sadoh WE, Fawole AO, Sadoh AE, Oladimeji AO, Sotiloye OS. Practice of universal precautions among healthcare workers. Journal of the National Medical Association. 2006;98(5):722. pmid:16749647
  28. 28. Kommogldomo ED. Needle stick and sharps injuries among health care workers at the 37 military hospital. Doctoral Dissertation. University of Ghana. Accera 2016.
  29. 29. Adane M, Mengistie B, Mulat W, Kloos H, Medhin G. Utilization of health facilities and predictors of health-seeking behavior for under-five children with acute diarrhea in slums of Addis Ababa, Ethiopia: A community-based cross-sectional study. J Health Popul Nutr. 2017;36(9).
  30. 30. Hosmer J, Lemeshow S, Sturdivant R. Applied logistic regression. 3rd ed. Hoboken, NJ: John Wiley and Sons 2013.
  31. 31. WMA. World Medical Associations Declaration of Helsinki. Ethical principles for medical research involving human subjects, 6th revision. Helsinki, Finland. 2008.
  32. 32. Council for International Organizations of Medical Sciences. International ethical guidelines for biomedical research involving human subjects. Bull Med Ethics. 2002;182(1):7–23. pmid:14983848
  33. 33. Weldesamuel E, Gebreyesus H, Beyene B, Teweldemedhin M, Welegebriel Z, Tetemke D. Assessment of needle stick and sharp injuries among health care workers in central zone of Tigray, northern Ethiopia. BMC Res Notes. 2019;12(654). pmid:31604448
  34. 34. Salelkar S, Motghare D, Kulkarni M, Vaz F. Study of needle stick injuries among health care workers at a tertiary care hospital. Indian J Public Health. 2010;54(1):18. pmid:20859044
  35. 35. Gaogoi J, Ahmed S, Saikia H, Sarma R. Study on knowledge, attitude, practice and prevalence of needle stick injuries among healthcare workers in a tertiary care hospital of Assam. Int J Public Health Institution. 2017;4:2031–35.
  36. 36. Voide C, Darling KE, Kenfak-Foguena A, Erard V, Cavassini M, Lazor-Blanchet C. Underreporting of needlestick and sharps injuries among healthcare workers in a Swiss University Hospital. Swiss Med Wkly. 2012;142(w13523):1–7.
  37. 37. Aderaw Z. Assessment on magnitude of sharp and needle stick injuries and asociated factors among healthcare workers in East Gojjam zone health institutions, Amhara Regional State, Ethiopia. Glob J Med Res. 2013;13(3).
  38. 38. Bekele T, Gebremariam A, Kaso M, Ahmed K. Factors associated with occupational needle stick and sharps injuries among hospital healthcare workers in Bale zone, Southeast Ethiopia PLoS ONE 2015;10(10):e0140382. pmid:26469776
  39. 39. Garus-Pakowska A, Górajski M. Epidemiology of needlestick and sharp injuries among health care workers based on records from 252 hospitals for the period 2010–2014, Poland. BMC Public Health. 2019;19(634). pmid:31126266
  40. 40. Motaarefi H, Mahmoudi H, Mohammadi E, Hasanpour-Dehkordi A. Factors associated with needlestick injuries in health care occupations. A syestematic review J Clin Diagn Res. 2016;10(8):1–4. pmid:27656466
  41. 41. Cho E, Lee H, Choi M, Park SH, Yoo IY, Aiken LH. Factors associated with needlestick and sharp injuries among hospital nurses: A cross sectional questionnaire study in South Korea. Int J Nurs Stud. 2014;50(8):1025–32.
  42. 42. Muralidhar S, Kumar Singh P, Jain R, Malhotra M, Bala M. Needle stick injuries among health care workers in a tertiary care hospital of India. Indian J Med Res. 2010;131(3):405–10.
  43. 43. Blenkharn JI. Sharps management and the disposal of clinical waste. Br J Nurs. 2009;18(14):860–64. pmid:19633596
  44. 44. Elmi S, Babaie J, Malek M, Motazedi Z, Shahsavari-Nia K. Occupational exposures to needle stick injuries among health care staff; A review study. J Anal Res Clin Med. 2018;6(1):1–6.
  45. 45. Kaweti G, Abegaz T. Prevalence of percutaneous injuries and associated factors among health care workers in Hawassa referral and adare District hospitals, Hawassa, Ethiopia, January 2014. BMC Public Health. 2015;16(8).
  46. 46. Bekele GA, Kaso M, Ahmed K. Factors Associated with Occupational Needle Stick And Sharps Injuries among hospital healthcare workers in Bale zone. PLoS ONE. 2015;1(11). pmid:26469776
  47. 47. Jahangiri M, Rostamabadi A, Hoboubi N, Tadayon N, Soleimani A. Needle stick injuries and their related safety measures among nurses in a university hospital, Shiraz, Iran. Safety and health at work. 2016;7(1):72–7. pmid:27014494
  48. 48. Pik E. Factors that contribute to the occurrence of work-related injuries among nurses. A systematic literature review. J Turkiturun Ammattikor Keakuolu. 2014: 2–51
  49. 49. Holla R, Unnikrishnan B, Ram P, Thapar R, Mithra P, Kumar N, et al. Occupational exposure to needle stick injuries among health care personnel in a tertiary care hospital: A cross sectional study. J Community Med Health Educ. 2014;S2(004).
  50. 50. Debra A. Blood-borne viruses and safety health hepatitis infection control and needle stick injuries prevention sharps injuries. Gudline of needle stick injury: 49–58. 2012.
  51. 51. Wang C, Huang L, Li J, Dai J. Relationship between psychosocial working conditions, stress perception, and needle-stick injury among healthcare workers in Shanghai. BMC Public Health. 2019;19(874).