The Epidemiology of Injuries in Adults in Nepal: Findings from a Hospital-Based Injury Surveillance Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Setting
2.2. Development and Evaluation of the Surveillance Model
2.3. Data Collection
2.4. Data Analysis
3. Results
3.1. Epidemiology of Adult Injuries
3.1.1. Demographics
3.1.2. Mechanism of Injury by Age and Sex
3.1.3. Association between Demographics and Injury Severity
3.1.4. Outcomes of Injury
3.2. Findings of the Process Evaluation
Injury data collection work might be difficult for clinical staff in the existing system. They might feel huge pressure if it is being added to their responsibilities. It might be difficult for them to treat the patient and collect the data at the same time.(Data collector, female, Hetauda Hospital)
Many patients visit the emergency department, and sometimes it is extremely busy. Most of the time, only two clinical staff are on duty to provide emergency care. If they [clinical staff] are required to collect data in such a situation, they will not have enough time to do so.(Data collector, female, Chure Hill Hospital)
The government has not provided additional funding for this [injury surveillance] programme. The government only budgets for its own programmes, and each programme has its own staff.(Paramedic, male, Hetauda Hospital)
I really like this programme. This is the first time such a programme has been conducted here. We would be able to learn about the number of injury incidents and the circumstances surrounding them. Similarly, we would know how to improve our emergency care services.(ED nurse, female, Chure Hill Hospital)
There are ten doctors in this hospital, and only a few of them are familiar with injury surveillance. Others who are uninterested in injury surveillance are unaware of the importance of data and how data collectors are performing their work.(Senior doctor, male, Chure Hill Hospital)
If the surveillance system is a government programme overseen by the Ministry of Health, it must be managed by the hospital. All of the staff will follow the system as if it were their own programme … Injury surveillance in all hospitals is possible if it is led by a higher authority, such as the government or a ministry.(Senior doctor, male, Hetauda Hospital)
Having these data collectors with medical knowledge was extremely beneficial to us. They assist us in the morning and evening, in busy hours, and during emergencies, which is a good thing.(Senior doctor, male, Hetauda Hospital)
Data collection has become simple because the data collectors come from a medical background. It would have been difficult for them if they did not come from a medical background. Because our subject is injury, it is simple for medical background staff to collect data.(Study team member, female, MIRA/NIRC)
We have sought assistance from police officers on occasion. Police officers, like us, are required to record cases such as road traffic injuries. They do not, however, have to collect information as thoroughly as we do.(Data collector, female, Chure Hill Hospital)
In the mortuary case, police introduce our data collectors to the deceased person’s relative and request them to provide information. It has simplified things.(ED nurse, male, Hetauda Hospital)
I enjoyed collecting data on tablets. Because of the functionality of the REDCap software, it is simple to collect data.(Data collector, female, Hetauda Hospital)
Yes, some of the cases have been missed. It usually happens when a large number of patients present at the emergency department at the same time. Sometimes serious injury cases are immediately referred to another hospital, and we are not aware of these cases because we are busy collecting data on other cases. We only knew about those cases while going through the register.(Data collector, female, Hetauda Hospital)
Collecting data with the relative of a deceased person is quite a difficult task, as they are in shock. Additionally, the relatives of a deceased person leave immediately after post-mortem. They do not wait for us.(Study team member, female, MIRA/NIRC)
4. Discussion
Strengths and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Age and Sex | Total | Male | Female | |||
---|---|---|---|---|---|---|
Years | n | Rate/1000 (95% CI) | n | Rate/1000 (95% CI) | n | Rate/1000 (95% CI) |
18–29 | 2950 | 32.6 (31.5–33.8) | 2048 | 48.6 (46.6–50.7) | 902 | 18.7 (17.5–19.9) |
30–44 | 2378 | 32.0 (30.8–33.3) | 1524 | 42.8 (40.7–44.9) | 854 | 22.1 (20.6–23.5) |
45–59 | 1285 | 26.4 (25.0–27.9) | 778 | 31.1 (28.9–33.2) | 507 | 21.5 (19.7–23.4) |
60 & above | 845 | 25.7 (24.0–27.4) | 459 | 27.9 (25.4–30.4) | 386 | 23.5 (21.2–25.8) |
Total | 7458 | 30.3 (29.6–31.0) | 4809 | 40.4 (39.2–41.5) | 2649 | 20.9 (20.0–21.7) |
Median (IRQ *) | 33 years (25–47 years) | 32 years (24–45 years) | 36 years (26–50 years) |
Age Groups, Sex Intent, and Mechanisms | 18–29 Years | 30–44 Years | 45–59 Years | ≥60 Years | Total | Male | Female | Male-to-Female Ratio |
---|---|---|---|---|---|---|---|---|
n (rate/1000) | n (rate/1000) | n (rate/1000) | n (rate/1000) | n (rate/1000) | n (rate/1000) | n (rate/1000) | M:F | |
Unintentional | ||||||||
Road traffic injury | 1005 (11.1) | 686 (9.2) | 291 (6.0) | 130 (4.0) | 2112 (8.6) | 1628 (13.7) | 484 (3.8) | 3.4:1 |
Fall | 460 (5.1) | 504 (6.8) | 339 (7.0) | 332 (10.1) | 1635 (6.6) | 847 (7.1) | 788 (6.2) | 1.1:1 |
Animal/insect-related | 408 (4.5) | 396 (5.3) | 288 (5.9) | 201 (6.1) | 1293 (5.3) | 700 (5.9) | 593 (4.7) | 1.2:1 |
Stabbed, cut, or pierced | 279 (3.1) | 215 (2.9) | 108 (2.2) | 47 (1.4) | 649 (2.6) | 493 (4.1) | 156 (1.2) | 3.2:1 |
Injured by a blunt object | 209 (2.3) | 157 (2.1) | 55 (1.1) | 46 (1.4) | 467 (1.9) | 374 (3.1) | 93 (0.7) | 4.0:1 |
Poisoning † | 28 (0.3) | 23 (0.3) | 11 (0.2) | 10 (0.3) | 72 (0.3) | 35 (0.3) | 37 (0.3) | 0.9:1 |
Electrocution | 35 (0.4) | 17 (0.2) | 6 (0.1) | 5 (0.2) | 63 (0.3) | 40 (0.3) | 23 (0.2) | 1.7:1 |
Fire, burn, or scald | 18 (0.2) | 16 (0.2) | 15 (0.3) | 10 (0.3) | 59 (0.2) | 33 (0.3) | 26 (0.2) | 1.3:1 |
Suffocation or choking | 5 (0.1) | 15 (0.2) | 9 (0.2) | 4 (0.1) | 33 (0.1) | 18 (0.2) | 15 (0.1) | 1.2:1 |
Other | 16 (0.2) | 20 (0.3) | 10 (0.2) | 5 (0.2) | 51 (0.2) | 28 (0.2) | 23 (0.2) | 1.2:1 |
Total | 2463 (27.3) | 2049 (27.6) | 1132 (23.3) | 790 (24.0) | 6434 (26.1) | 4196 (35.2) | 2238 (17.6) | 1.9:1 |
Self-harm | ||||||||
Poisoning ‡ | 138 (1.5) | 82 (1.1) | 41 (0.8) | 18 (0.5) | 279 (1.1) | 100 (0.8) | 179 (1.4) | 0.6:1 |
Hanging | 21 (0.2) | 19 (0.3) | 13 (0.3) | 6 (0.2) | 59 (0.2) | 32 (0.3) | 27 (0.2) | 1.2:1 |
Stabbed, cut, or pierced | 40 (0.4) | 11 (0.1) | 3 (0.1) | 0 (0.0) | 54 (0.2) | 40 (0.3) | 14 (0.1) | 2.9:1 |
Other | 9 (0.1) | 6 (0.1) | 1 (0.0) | 0 (0.0) | 16 (0.1) | 12 (0.1) | 4 (0.0) | 3.0:1 |
Total | 208 (2.3) | 118 (1.6) | 58 (1.2) | 24 (0.7) | 408 (1.7) | 184 (1.5) | 224 (1.8) | 0.8:1 |
Assault | ||||||||
Bodily force | 206 (2.3) | 167 (2.2) | 69 (1.4) | 21(0.6) | 463 (1.9) | 321 (2.7) | 142 (1.1) | 2.3:1 |
Injured by a blunt object | 36 (0.4) | 27 (0.4) | 14 (0.3) | 6(0.2) | 83 (0.3) | 57 (0.5) | 26 (0.2) | 2.2:1 |
Stabbed, cut, or pierced | 29 (0.3) | 14 (0.2) | 12 (0.2) | 4(0.1) | 59 (0.2) | 45 (0.4) | 14 (0.1) | 3.2:1 |
Other | 8 (0.1) | 3 (0.0) | 0 (0.0) | 0(0.0) | 11 (0.0) | 6 (0.1) | 5 (0.0) | 1.2:1 |
Total | 279 (3.1) | 211 (2.8) | 95 (2.0) | 31(0.9) | 616 (2.5) | 429 (3.6) | 187 (1.5) | 2.3:1 |
Characteristics | Minor or No Apparent Injury (Total = 4551) n (%) | Moderate or Severe Injury (Total = 2897) n (%) | Odds Ratio (95% CI) | p-Value |
---|---|---|---|---|
Sex | ||||
Male | 2886 (60.1) | 1915 (39.9) | 1.35 (1.20–1.52) | 0.000 |
Female | 1665 (62.9) | 982 (37.1) | 1.00 (reference) | N/A |
Age groups (years) | ||||
18–29 | 1819 (61.7) | 1128 (38.3) | 1.25 (1.03–1.51) | 0.024 |
30–44 | 1465 (61.7) | 910 (38.3) | 1.13 (0.94–1.36) | 0.190 |
45–59 | 778 (60.6) | 506 (39.4) | 1.03 (0.86–1.24) | 0.730 |
≥60 | 489 (58.1) | 353 (41.9) | 1.00 (reference) | N/A |
Ethnicity/caste * | ||||
Dalit | 198 (55.8) | 157 (44.2) | 1.33 (1.06–1.67) | 0.014 |
Janajati | 2061 (58.5) | 1465 (41.5) | 1.25 (1.12–1.39) | 0.000 |
Madhesi | 253 (57.9) | 184 (42.1) | 1.26 (1.02–1.56) | 0.031 |
Muslim | 102 (62.2) | 62 (37.8) | 1.01 (0.73–1.41) | 0.935 |
Brahmin/Chhetri | 1845 (65.6) | 967 (34.4) | 1.00 (reference) | N/A |
Others | 84 (58.7) | 59 (41.3) | 1.26 (0.89–1.78) | 0.198 |
Education ** | ||||
No formal education | 1446 (55.2) | 1175 (44.8) | 1.70 (1.41–2.05) | 0.000 |
Primary school | 1257 (62.0) | 772 (38.0) | 1.19 (1.00–1.41) | 0.048 |
Secondary school | 1065 (65.8) | 554 (34.2) | 1.03 (0.87–1.22) | 0.720 |
Post-secondary school | 781 (67.3) | 380 (32.7) | 1.00 (reference) | N/A |
Occupation *** | ||||
Mainly unemployed | 1064 (57.6) | 783 (42.4) | 1.51 (1.20–1.90) | 0.000 |
Employed salaried | 1101 (63.6) | 629 (36.4) | 1.20 (0.96–1.49) | 0.094 |
Daily wage earners | 809 (60.1) | 538 (39.9) | 1.08 (0.85–1.36) | 0.523 |
Agricultural labourer | 681 (59.1) | 472 (40.9) | 1.23 (0.96–1.58) | 0.109 |
Business owner | 467 (62.8) | 277 (37.2) | 1.19 (0.93–1.53) | 0.167 |
Student | 385 (68.6) | 176 (31.4) | 1.00 (reference) | N/A |
Pensioner | 44 (75.9) | 14 (24.1) | 0.69 (0.36–1.33) | 0.265 |
Participant Number | Interview Participant’s Role in Hospital/Study | Based | Gender | Age (Years) |
---|---|---|---|---|
P1 | Data collector | Chure Hill Hospital | Female | 20–25 |
P2 | Data collector | Chure Hill Hospital | Female | 20–25 |
P3 | Data collector | Hetauda Hospital | Female | 35–40 |
P4 | Data collector | Hetauda Hospital | Female | 20–25 |
P5 | ED nurse | Chure Hill Hospital | Female | 30–35 |
P6 | Senior nurse | Chure Hill Hospital | Female | 25–30 |
P7 | Manager | Chure Hill Hospital | Male | 25–30 |
P8 | Senior doctor | Chure Hill Hospital | Male | 30–35 |
P9 | Manager | Hetauda Hospital | Male | 40–45 |
P10 | Senior doctor | Hetauda Hospital | Male | 45–50 |
P11 | ED nurse | Hetauda Hospital | Male | 40–45 |
P12 | Paramedic | Hetauda Hospital | Male | 55–60 |
P13 | Study team member | MIRA/NIRC | Female | 40–45 |
P14 | Study team member | MIRA/NIRC | Male | 45–50 |
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Bhatta, S.; Magnus, D.; Mytton, J.; Joshi, E.; Bhatta, S.; Adhikari, D.; Manandhar, S.R.; Joshi, S.K. The Epidemiology of Injuries in Adults in Nepal: Findings from a Hospital-Based Injury Surveillance Study. Int. J. Environ. Res. Public Health 2021, 18, 12701. https://doi.org/10.3390/ijerph182312701
Bhatta S, Magnus D, Mytton J, Joshi E, Bhatta S, Adhikari D, Manandhar SR, Joshi SK. The Epidemiology of Injuries in Adults in Nepal: Findings from a Hospital-Based Injury Surveillance Study. International Journal of Environmental Research and Public Health. 2021; 18(23):12701. https://doi.org/10.3390/ijerph182312701
Chicago/Turabian StyleBhatta, Santosh, Dan Magnus, Julie Mytton, Elisha Joshi, Sumiksha Bhatta, Dhruba Adhikari, Sunil Raja Manandhar, and Sunil Kumar Joshi. 2021. "The Epidemiology of Injuries in Adults in Nepal: Findings from a Hospital-Based Injury Surveillance Study" International Journal of Environmental Research and Public Health 18, no. 23: 12701. https://doi.org/10.3390/ijerph182312701
APA StyleBhatta, S., Magnus, D., Mytton, J., Joshi, E., Bhatta, S., Adhikari, D., Manandhar, S. R., & Joshi, S. K. (2021). The Epidemiology of Injuries in Adults in Nepal: Findings from a Hospital-Based Injury Surveillance Study. International Journal of Environmental Research and Public Health, 18(23), 12701. https://doi.org/10.3390/ijerph182312701