Epidemiology and outcomes of brain trauma in rural and urban populations: a systematic review and meta-analysis

Figures & data

Figure 1. PRISMA Flow Diagram of the study selection process. A total of 1,310 studies were evaluated for rural/urban differences in patients with brain trauma. After title and abstract screening, 90 full-text articles were reviewed, 36 of which were included in the systematic review and meta-analysis after exclusions. CINAHL, Cumulative Index of Nursing and Allied Health; EBSCO, Elton B. Stephens Company; MOI, mechanism of injury.

Table 1. Study characteristics and quality assessment.

Author	Year	Study Design	Year Range	Sample	Region^¶	Patient Source	Follow-up	Rural/Urban Classification	Quality
Agrawal et al. (14)	2017	Prospective single-center cohort	6 months	337	Asia	ED	Hospital Discharge	Not defined	Moderate
Andelic et al. (16)	2012	Population-based prospective	2009–2010 (2 yr)	359	Europe	Hospital	Hospital Discharge	Region-specific^§	High
Asemota et al. (26)	2013	Population-based retrospective	2005–2009 (4 yr)	139,798	North America	Hospital	Hospital Discharge	Not defined	Moderate
Berry et al. (5)	2010	Population-based retrospective	2000–2006 (6 yr)	95,485	Oceania	Hospital	None	Formal Classification^‡	Moderate
Brown et al. (18)	2019	Population-based retrospective	2008–2014 (7 yr)	NR	North America	Death registry	Death	Formal Classification	Moderate
Chan et al. (43)	2005	Prospective multi-center cross-sectional	1998–2001 (4 yr)	165	Asia	ED	None	Region-specific	High
Chapital et al. (20)	2007	Retrospective single-center cohort	2000–2004 (5 yr)	3,447	North America	Hospital	Hospital Discharge	Region-specific	High
Cheng et al. (27)	2017	Population-based retrospective	2006–2013 (8 yr)	93,793	North America	Death registry	Death	Formal Classification	Moderate
Cheng et al. (45)	2020	Population-based retrospective	1999–2017 (19 yr)	99,796	Asia	Death registry	Death	Region-specific	Moderate
Chiang et al. (46)	2006	Population-based retrospective	2001–2004 (3 yr)	592	Asia	Hospital	Hospital Discharge	Region-specific	Moderate
Chiu et al. (19)	2007	Population-based retrospective	2001 (1 yr)	7,228	Asia	Hospital/death certificates	Hospital Discharge	Region-specific	High
Daugherty et al. (28)	2021	Population-based retrospective	2016–2018 (3 yr)	181,227	North America	Death registry	Death	Formal Classification	Moderate
Feigin et al. (38)	2013	Population-based prospective and retrospective	2010–2011 (1 yr)	1,369	Oceania	All Community	None	Region-specific	High
Gabella et al. (15)	1997	Population-based retrospective	1991–1992 (2 yr)	7,056	North America	Hospital/death certificates	Hospital Discharge/Death	Formal Classification	High
Gontkovsky et al. (29)	2006	Prospective single-center cohort	1998–2002 (3.5 yr)	111	North America	Rehabilitation	1 yr	Goodall et al. method^63	High
Graves et al. (30)	2019	Retrospective multi-center cohort	2007–2011 (5.5 yr)	387,846	North America	Hospital	180 days	Region-specific	High
Halldorsson et al. (44)	2007	Population-based prospective	1992–1993 (1 yr)	550	Europe	Hospital/death registry	Death	Region-specific	High
Harradine et al. (39)	2004	Prospective multi-center longitudinal	1999–2001 (2 yr)	198	Oceania	Rehabilitation	18 mths	Formal Classification	High
Harrison et al. (40)	2012	Population-based retrospective	2000–2006 (6 yr)	103,782	Oceania	Hospital	Hospital Discharge	Formal Classification	High
Johnstone et al. (31)	2003	Prospective single-center longitudinal	2 yr	78	North America	Rehabilitation	VR Completion	Formal Classification	Moderate
Karwat et al^.† (11,49)	2009	Population-based retrospective	1999–2002 (4 yr)	265	Europe	Hospital	Hospital Discharge/Death	Not defined	Moderate
Leonhard et al. (32)	2015	Population-based retrospective	2009–2012 (4 yr)	2,794	North America	Hospital	Death	Formal Classification	High
Maier et al. (17)	2014	Retrospective multi-center cross-sectional	2005–2008 (R) 2003–2007 (U) (3.5 yr)	680	Africa	Hospital	None	Region-specific	Moderate
Ponsford et al. (6)	2012	Retrospective single-center cohort	1984–2006 (24 yr)	959	Oceania	Rehabilitation	2 yr	Region-specific	High
Pozzato et al. (21)	2019	Population-based retrospective	2007 (1 yr)	6,827	Oceania	Hospital	Hospital Discharge	Formal Classification	Moderate
Ratliff et al. (33)	2021	Population-based retrospective	2008–2014 (7 yr)	3,180	North America	Death registry	Death	Formal Classification	Moderate
Reid et al. (34)	2001	Population-based retrospective	1993 1 yr)	977	North America	Hospital/death certificates	Hospital Discharge/Death	Goldsmith et al. method^64	High
Ring et al. (41)	1986	Retrospective multi-center cohort	1997–1978 (2 yr)	991	Oceania	Hospital	Hospital Discharge/Death	Region-specific	High
Robertson & McConnel (35)	2011	Retrospective single-center cohort	5 yr	444	North America	Hospital	Hospital Discharge	Formal Classification	Moderate
Schootman & Fuortes (36)	2000	Population-based retrospective	1995–1997 (3 yr)	4,300,000	North America	Ambulatory care	End of Care Episode	Region-specific	Moderate
Simpson et al. (42)	2016	Prospective. multi-center cross-sectional	2007–2008 (1 yr)	503	Oceania	Rehabilitation	6 mths (minimum)	Formal Classification	High
Stewart et al. (37)	2014	Retrospective single-center cross-sectional	2006–2011 (6 yr)	2,112	North America	ED	None	Region-specific	High
Tesfaw et al. (47)	2021	Prospective single-center cross-sectional	2019 (2 mths)	370	Africa	Hospital	Hospital Discharge	Not defined	Moderate
Woodward et al. (22)	1984	Population-based retrospective	1980–1981 (2 yr)	12,201	Oceania	Hospital	Hospital Discharge	Formal Classification	Moderate
Yates et al. (48)	2006	Retrospective single-center cohort study	1997–2003 (6 yr)	11,700	Europe	ED	None	Not defined	Moderate

^†Karwat et al. (2009A and 2009B) report different outcomes on the same patient population, and are therefore considered as one study. ^¶ Locations of Asian studies included India (14), Malaysia (43), China (45), and Taiwan (19,46). European study locations were Norway (16), Iceland (44), Poland (11,49), and the United Kingdom (48). Seven of the North American studies were national studies (18,26–28,30,33,36), with others state-based (Hawaii (20), Colorado (15), Mississippi (29), Missouri (31), Oregon (32), Minnesota (34), and Texas (35)), and one Canadian study (37). Oceania studies were all conducted in Australia with the exception of Feigin et al. (38) which was a New Zealand study. The African studies were conducted in Tanzania (17) and Ethiopia (47). ^§ Authors have designated a rural or urban label to a specific city, county or region based on its population, geographic or service provision characteristics. ^‡ Authors have utilized a preexisting nationally recognized method of classification. ED, emergency department; VR, Vocational Rehabilitation; R, rural; U, urban.

Figure 2. Forest plot demonstrating the mean difference in age (years) calculated using the random effects model. There was no statistical difference in age between rural and urban patients with brain trauma (MD: 1.10; 95% CI − 3.17, 5.37; p = 0.61). Mean [SD] for Stewart 2014 (37) was calculated using the methodology of Wan et al (25). SD, standard deviation; CI, confidence interval; I², test of heterogeneity; MD, mean difference.

Figure 3. Forest plot demonstrating the odds ratio of male sex in rural and urban brain trauma populations with subgroup analysis of pediatric/adolescent cohorts, adult cohorts, and studies incorporating all ages. The proportion of males suffering brain trauma was comparable across rural and urban areas, regardless of age. SD, standard deviation; CI, confidence interval; I², test of heterogeneity.

Table 2. Patient characteristics.

Author	Year	Age Group	Age Range (yr)	Male Sex (%)	Severity	Rural/Urban Ratio (%)
Agrawal et al. (14)	2017	All	1–90	271 (80.4%)	All	274 (72.6%)/54 (27.4%)
Andelic et al. (16)	2012	Adult	>16	214 (77%)	Severe	82 (29%)/196 (71%)
Asemota et al. (26)	2013	Adolescent/Young Adult	10–19	99,047 (71%)	All	7,631 (5%)/132,167 (95%)
Berry et al. (5)	2010	Pediatric	0–14	61,179 (64%)	All	11,160 (50.9%)/10,719 (50.0%)
Brown et al. (18)	2019	All	NR	NR	All	NR
Chan et al. (43)	2005	Pediatric/Adolescent	2–18	NR	Mild	112 (42%)/153 (58%)
Chapital et al. (20)	2007	All	0–106	2573 (75%)	All	358 (10.4%)/3,089 (89.6%)
Cheng et al. (27)	2017	All	0->75	NR	NR	NR
Cheng et al. (45)	2020	Adolescent/Young Adult	0–19	NR	All	NR
Chiang et al. (46)	2006	Adolescents	13–18	306 (65%)	All	131 (22%)/469 (78%)
Chiu et al. (19)	2007	All	NR	4698 (65%)	All	1,474 (20.4%)/5,754 (79.6%)
Daugherty et al. (28)	2021	All	NR	NR	All	NR
Feigin et al. (38)	2013	All	0->65	856 (63%)	All	361 (26.4%)/1,008 (73.6%)
Gabella et al. (15)	1997	All	0->65	4598 (67%)	All	1,338 (19%)/5,525 (81%)
Gontkovsky et al. (29)	2006	Adult	>16	79 (71%)	All	NR
Graves et al. (30)	2019	Pediatric/Adolescent	0–18	238,994 (62%)	Mild	49,643 (13%)/338,203 (87%)
Halldorsson et al. (44)	2007	Pediatric/Adolescent	0–19	NR	All	141 (26%)/409 (74%)
Harradine et al. (39)	2004	Adult	16–65	155 (78%)	Severe	51 (26%)/147 (74%)
Harrison et al. (40)	2012	Adolescent/Young Adult	15–24	NR	All	13,146 (47.2%)/14,728 (52.8%)
Johnstone et al. (31)	2003	Adult	NR	55 (71%)	NR	28 (35.9%)/50 (64.1%)
Karwat et al^.† (11,49)	2009	All	0->65	204 (77%)	NR	90 (34%)/175 (66%)
Leonhard et al. (32)	2015	Pediatric/Adolescent	0–19	1879 (67%)	All	799 (28.6%)/1,995 (71.4%)
Maier et al. (17)	2014	All	0.2–100	NR	NR	248 (36.5%)/432 (63.5%)
Ponsford et al. (6)	2012	All	11–89	671 (70%)	All	314 (32.7%)/645 (67.3%)
Pozzato et al. (21)	2019	All	0->70	2180 (74.5%)	All	2,240 (33.3%)/4,482 (66.7%)
Ratliff et al. (33)	2021	All	NR	NR	All	NR
Reid et al. (34)	2001	Pediatric/Adolescent	0–19	NR	All	343 (35.1%)/634 (64.9%)
Ring et al. (41)	1986	All	0->75	721 (73%)	All	309 (31.2%)/682 (68.8%)
Robertson & McConnel (35)	2011	Pediatric/Adolescent	0–18	298 (67%)	Severe	38 (8.6%)/406 (91.4%)
Schootman & Fuortes (36)	2000	All	0->75	NR	All	NR
Simpson et al. (42)	2016	Adult	18–65	389 (77%)	Severe	171 (34%)/332 (66%)
Stewart et al. (37)	2014	Pediatric/Adolescent	0–18	1415 (67%)	Mild	387 (19%)/1,687 (81%)
Tesfaw et al. (47)	2021	Adult	>18	265 (72%)	All	259 (70%)/111 (30%)
Woodward et al. (22)	1984	All	0->75	NR	NR	3,971 (32.5%)/8,230 (67.5%)
Yates et al. (48)	2006	All	0->85	NR	NR	NR

^†Karwat et al. (2009A and 2009B) report different outcomes on the same patient population, and are therefore considered as one study. NR, not reported.

Table 3. Incidence Rate of Brain Trauma (/100,000 persons) in Rural and Urban Populations.

Author	Year	Rural	Urban	p Value
Andelic et al^.† (16)	2012	5.9 (North) 4.3 (Central)	5.0 (West) 4.1 (Southeast)	NR
Chiu et al. (19)	2007	417	218	NR
Feigin et al^.¶ (38)	2013	73	31	NR
Gabella et al^.† (15)	1997	123.9 (Rural non-remote) 172.1 (Rural remote)	97.8 (CMSA) 94.7 (Other metro)	NR
Halldorsson et al. (44)	2007	367	864	NR
Harrison et al. (40)	2012	664.2 (Inner regional) 949.9 (Outer regional) 366.9 (Remote) 1680.2 (Very remote)	522.1 (Major city)	NR
Leonhard et al. (32)	2015	107	71 (Large metropolitan) 59 (Small/medium metropolitan)	NR
Reid et al. (34)	2001	76.1	72.4	0.046
Schootman & Fuortes (36)	2000	410	570	NR
Stewart et al. (37)	2014	220	350	NR
Woodward et al. (22)	1984	570	430	<0.001
Yates et al. (48)	2006	223.8 (All BI) 29.6 (MSBI)	826.9 (All BI) 55.6 (MSBI)	NR

^†Age-adjusted. ^¶ Moderate-severe brain injury. NR, not reported; CMSA, Consolidated metropolitan statistical area; BI, brain injury; MSBI, moderate-severe brain injury.

Figure 4. Forest plot demonstrating the odds ratio of transport being the cause of brain trauma in rural and urban populations with subgroup analysis of pediatric/adolescent cohorts, adult cohorts, and studies incorporating all ages. Overall, rural residents were significantly more likely to suffer brain trauma resulting from transport accidents, particularly those in pediatric and adolescent age groups (OR: 1.62; 95% CI 1.33, 1.98; p < 0.00001). CI, confidence interval; I², test of heterogeneity; OR, odds ratio.

Figure 5. Forest plots showing types of transport accidents causing traumatic brain injury in rural and urban populations. (A), Car; (B), Pedestrian; (c), Other motorized vehicle; (D), Bicycle. Pedestrian-related brain injuries were 64% more likely in urban environments (p = 0.008), whereas motorized vehicles such as all-terrain vehicles, quad bikes, and motorcycles, were responsible for more injuries in rural areas (OR: 3.63; 95% CI 1.58, 8.35; p = 0.002). CI, confidence interval; I², test of heterogeneity; OR, odds ratio.

Figure 6. Forest plot demonstrating the odds ratio of falls being the cause of brain trauma in rural and urban populations with subgroup analysis of pediatric/adolescent cohorts, adult cohorts, and studies incorporating all ages. Overall, urban residents were 27% more likely to suffer brain trauma resulting from falls (p < 0.00001). The odds of fall-induced brain trauma was significantly less in rural children and adolescents (OR: 0.65; 95% CI 0.52, 0.81; p < 0.0002). CI, confidence interval; I², test of heterogeneity; OR, odds ratio.

Figure 7. Forest plot demonstrating the odds ratio of assault being the cause of brain trauma in rural and urban populations with subgroup analysis of mild, severe, and injury severities. Overall, assault-related brain injury was comparable across rural and urban populations, except mild brain injuries caused by assault which were ~ 50% less likely in rural areas (p = 0.03). CI, confidence interval; I², test of heterogeneity.

Figure 8. Forest plots showing no difference in (A) sports-related and (B) other causes of brain trauma in rural and urban populations. Other causes included exposure to animal and inanimate mechanical forces, work-related accidents, and use of firearms. CI, confidence interval; I², test of heterogeneity.

Figure 9. Forest plots showing measures of brain injury severity in rural and urban populations. (A), Proportion of severe brain injury (GCS 3–8); (B), GCS (mean [SD); (C), Normal CT findings; (D), CT-diagnosed skull fracture; (E), CT-diagnosed ICH. Rural residents were significantly more likely to suffer severe brain trauma (OR: 1.28; 95% CI 1.04, 1.58; p = 0.02), and less likely to have a normal CT (OR: 0.52; 95% CI 0.41, 0.67; p < 0.00001). Mean [SD] GCS for Harradine 2004 (39) was calculated using the methodology of Wan et al (25). GCS, Glasgow Coma Scale; CT, computed tomography; ICH, intracranial hemorrhage; CI, confidence interval; I², test of heterogeneity; OR, odds ratio.

Figure 10. Forest plots showing clinical symptoms after brain injury in rural and urban populations. (A), LOC/ALOC; (B), Headache; (C), Seizures; (D), Nausea/Vomiting. Rural residents were five-fold more likely to suffer loss of, or altered, consciousness (p = 0.04). Incidence of headache, seizures, and nausea or vomiting was similar in patients from rural and urban areas. LOC, loss of consciousness; ALOC, altered level of consciousness; CI, confidence interval; I², test of heterogeneity.

Figure 11. a, Forest plot showing mortality incidence in rural and urban brain trauma populations calculated using the random effects model. Mortality was comparable across rural and urban areas. b, Funnel plot of publication bias. CI, confidence interval; I², test of heterogeneity.

Table 4. Brain Trauma Mortality Rate in Rural and Urban Populations.

Author	Year	Rural	Urban	p Value
Brown et al. (18)	2019	22.32	18.22	<0.001
Cheng et al^.† (27)	2017	18.55	9.92	NR
Gabella et al^.† (15)	1997	25.5 (Rural, non-remote) 33.8 (Rural, remote)	18.1 (CMSA) 18.6 (Other metro)	NR
Leonhard et al^.¶ (32)	2015	2.5 [1.6–4.0]	1.00 (Large metro) 1.3 [0.6–2.8] (Small/medium metro)	0.001
Ratliff et al^.¶ (33)	2021	1.75 (1.66–1.84)	1.00 (Metro) 1.33 [1.29–1.36] (Nonmetro counties)	<0.001
Reid et al. (34)	2001	15.4	6.5	0.001

Data presented as Mortality/100,000 persons or Mortality Rate Ratio [95% CI]¶. † Age-adjusted. NR, not reported; CMSA, consolidated metropolitan statistical area; CI, confidence interval.

Figure 12. Forest plots showing outcomes after brain injury in rural and urban populations. a, Vegetative/severe disability; b, Good recovery; c, Length of hospital stay (days); d, Employed post-injury. Urban residents were more likely to have a good recovery (p = 0.003), and reduced hospital stay, however this difference was not statistically significant (MD: −3.23; 95% CI − 10.08, 3.63; p = 0.36). Mean [SD] LOS for Harradine 2004 (39) and Reid 2001 (34) was calculated using the methodology of Wan et al (25). LOS, length of stay; CI, confidence interval; I², test of heterogeneity; MD, mean difference.

Table

Table

Database Searched	Search Strategy
CINAHL <1982 to February 07, 2022>
Ovid Emcare <1995 to 2022 Week 4>	1exp head injury/ 2exp rural health/or exp rural population/ 31 and 2 4limit 3 to (human and English language)
Ovid MEDLINE® and Epub Ahead of Print, In-Process, In-Data-Review & Other Non-Indexed Citations, Daily and Versions < 1946 to February 04, 2022>	1exp Craniocerebral Trauma/ 2exp Rural Health/or exp Rural Population/ 31 and 2 4limit 3 to (English language and humans)
Scopus <1788 to February 07, 2022>	(‘head injur*’ OR ‘head trauma’ OR ‘traumatic brain injur*’ OR tbi) AND (rural OR remote) AND (LIMIT-TO (DOCTYPE, ‘ar’)) AND (LIMIT-TO (SUBJAREA, ‘MEDI’) OR LIMIT-TO (SUBJAREA, ‘NEUR’)) AND (LIMIT-TO (LANGUAGE, ‘English’)) AND (LIMIT-TO (EXACTKEYWORD, ‘Human’) OR LIMIT-TO (EXACTKEYWORD, ‘Humans’))

CINAHL, Cumulative Index of Nursing and Allied Health; EBSCO, Elton B. Stephens Company; TBI, traumatic brain injury.

Table

Selection
1	Is the study population likely to be representative of the whole population?
2	Was the non-exposed cohort (urban population) sourced from the same state/country or database?
3	Was the exposure ascertained through secure records, i.e., confirmed medical record?
4	Does the study specify the source of data?
5	Was the sample size appropriate for each cohort for statistical comparison of rural and urban populations?
6	Are inclusion and exclusion criteria clearly outlined?
7	Is the study population specifically sought for the purpose of the study i.e., not part of a larger shared database?
8	Is the date range of the data set clearly stated?
Comparability
9	Is the research methodology clearly stated?
10	Is the data collection methodology clearly stated?
11	Is the statistical methodology appropriate?
12	Does the study report demographics for both rural and urban populations to enable comparison?
13	Does the study report incidence/prevalence as well as mortality/other outcome measure?
14	Does the study state the method of determining head injury severity?
15	Does the study state the method of determining urban and rural classifications?
Outcome
16	Are the outcomes clearly stated and discussed in relation to the data collection?
17	Does the study report findings in relation to original aims?
18	Was follow-up long enough for outcomes to occur without missing data (e.g., mortality, length of stay)?
19	Were the differences between groups clinically meaningful? (i.e., was the clinical significance reported in addition to statistical significance)
20	Does the study account for confounding factors and is it considered in the analysis?

Table

Item	Recommendation	Reported on Page No
Reporting of background should include
1	Problem definition	4
2	Hypothesis statement	Not applicable
3	Description of study outcome(s)	4
4	Type of exposure or intervention used	Not applicable
5	Type of study designs used	Table 1
6	Study population	Table 1-Table 2
Reporting of search strategy should include
7	Qualifications of searchers (eg, librarians and investigators)	1 (Title page)
8	Search strategy, including time period included in the synthesis and key words	5, Appendix 2
9	Effort to include all available studies, including contact with authors	5
10	Databases and registries searched	5, Appendix 2
11	Search software used, name and version, including special features used	5, Appendix 2
12	Use of hand searching (eg, reference lists of obtained articles)	5
13	List of citations located and those excluded, including justification	8, Fig 1
14	Method of addressing articles published in languages other than English	5
15	Method of handling abstracts and unpublished studies	5
16	Description of any contact with authors	5, 8, Fig 1
Reporting of methods should include
17	Description of relevance or appropriateness of studies assembled for assessing the hypothesis to be tested	5
18	Rationale for the selection and coding of data (eg, sound clinical principles or convenience)	6
19	Documentation of how data were classified and coded (eg, multiple raters, blinding and interrater reliability)	5–6
20	Assessment of confounding (eg, comparability of cases and controls in studies where appropriate)	Table 3-Table 4
21	Assessment of study quality, including blinding of quality assessors, stratification or regression on possible predictors of study results	6, Appendix 3
22	Assessment of heterogeneity	6–7
23	Description of statistical methods (eg, complete description of fixed or random effects models, justification of whether the chosen models account for predictors of study results, dose-response models, or cumulative meta-analysis) in sufficient detail to be replicated	6–7
24	Provision of appropriate tables and graphics	Table 1-Table 4 Fig 1-12 Appendices 5–7
Reporting of results should include
25	Graphic summarizing individual study estimates and overall estimate	Fig 2-12
26	Table giving descriptive information for each study included	Table 1-Table 2
27	Results of sensitivity testing (eg, subgroup analysis)	8–10, 12, Fig 3, 4, 6, 7
28	Indication of statistical uncertainty of findings	8–12
Reporting of discussion should include
29	Quantitative assessment of bias (eg, publication bias)	8, 12, Table 1, Fig 11B
30	Justification for exclusion (eg, exclusion of non-English language citations)	5, Fig 1
31	Assessment of quality of included studies	8, Table 1
Reporting of conclusions should include
32	Consideration of alternative explanations for observed results	13–19
33	Generalization of the conclusions (ie, appropriate for the data presented and within the domain of the literature review)	17–19
34	Guidelines for future research	19
35	Disclosure of funding source	1

From: Stroup DF, Berlin JA, Morton SC, et al, for the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) Group. Meta-analysis of Observational Studies in Epidemiology. A Proposal for Reporting. JAMA. 2000;283(15):2008-2012. doi: 10.1001/jama.283.15.2008.

Table

Author	Year	Data Source(s)
Agrawal et al. (14)	2017	Prospective collection (single tertiary hospital)
Andelic et al. (16)	2012	Analysis of data from prospective population-based multicentre study
Asemota et al. (26)	2013	HCUP-NIS
Berry et al. (5)	2010	AIHW NHMD
Brown et al. (18)	2019	CDC WISQARS™
Chan et al. (43)	2005	Prospective collection (2 hospitals)
Chapital et al. (20)	2007	Queen’s Medical Center trauma database
Cheng et al. (27)	2017	CDC WONDER
Cheng et al. (45)	2020	China DSP
Chiang et al. (46)	2006	Taiwan Head Injury Registry + hospital records (24 hospitals)
Chiu et al. (19)	2007	Prospective collection (26 hospitals)
Daugherty et al. (28)	2021	CDC NVSS
Feigin et al. (38)	2013	CT/MRI records, hospital discharge registers, private hospitals, GP practices, rehabilitation centers, outpatient clinics, coroner/autopsy records, rest homes, community health services, schools, sports centers, ambulance services, prison, ACC database, death certificates, hospital separation data
Gabella et al. (15)	1997	Colorado surveillance system (hospital discharge data + death certificate data)
Gontkovsky et al. (29)	2006	NIDRR TBI Model System + participant/family member interviews
Graves et al. (30)	2019	MarketScan CCAE
Halldorsson et al. (44)	2007	Icelandic hospitals + EDs + healthcare centers + death register
Harradine et al. (39)	2004	Prospective collection (11 rehabilitation units)
Harrison et al. (40)	2012	AIHW NHMD
Johnstone et al. (31)	2003	Missouri Division of Vocational Rehabilitation
Karwat et al^.† (11,49)	2009	Lublin Regional Specialist Hospital records
Leonhard et al. (32)	2015	Oregon Trauma registry
Maier et al. (17)	2014	CT/MRI records (2 hospitals)
Ponsford et al. (6)	2012	Prospective collection (single rehabilitation center)
Pozzato et al. (21)	2019	NSW Department of Health hospital data
Ratliff et al. (33)	2021	CDC WISQARS™
Reid et al. (34)	2001	MDH TBI Registry + death certificates
Ring et al. (41)	1986	NSW Hospital Morbidity Statistics + hospital indices (133 hospitals) + death certificates
Robertson & McConnel (35)	2011	Children’s Medical Center Dallas trauma census
Schootman & Fuortes (36)	2000	NAMCS & NHAMCS
Simpson et al. (42)	2016	Prospective collection (11 rehabilitation units) + NSW electronic database
Stewart et al. (37)	2014	NACRS
Tesfaw et al. (47)	2021	Prospective collection (single tertiary hospital)
Woodward et al. (22)	1984	South Australian Health Commission hospital separation discharges/transfers/deaths
Yates et al. (48)	2006	Royal Devon and Exeter Hospital ED database

^†Karwat et al. (2009A and 2009B) report different outcomes on the same patient population, and are therefore considered as one study. HCUP-NIS, Healthcare Cost and Utilization Project Nationwide Inpatient Sample; AIHW NHMD, Australian Institute of Health and Welfare National Hospital Morbidity Database; CDC, Centers for Disease Control and Prevention; WISQARS™, Web-based Injury Statistics Query and Reporting; WONDER, Wide-ranging Online Data for Epidemiological Research; DSP, Disease Surveillance Points; NVSS, National Vital Statistics System; CT, computed tomography; MRI, magnetic resonance imaging; GP, General Practitioner; ACC, Accident Compensation Corporation; NIDRR, National Institute in Disability and Rehabilitation Research; TBI, traumatic brain injury; CCAE, Commercial Claims and Encounters database; ED, emergency department; NSW, New South Wales; MDH, Minnesota Department of Health; NAMCS, National Ambulatory Care Survey; NHAMCS, National Hospital Ambulatory Care Survey; NACRS, National Ambulatory Care Reporting System.

Table

Author	Year	Inclusion Criteria	Exclusion Criteria
Agrawal et al. (14)	2017	Consent provided	NR
Andelic et al. (16)	2012	≥16 yr; Norwegian resident; admitted within 72 h after injury; ICD-10 S06.0-S06.9; severe TBI	Injured abroad; progressive neurological diseases/injuries; severe psychiatric diseases; severe alcohol &/or narcotics abuse, homeless; no consent
Asemota et al. (26)	2013	10–19 yr; primary or secondary diagnosis of TBI; ICD-9-CM 800.00–804.09, 850.0–854.19	Interhospital transfers; discharged directly from ED; treated in outpatient settings
Berry et al. (5)	2010	0–14 yr; ICD-9-CM 800.0–801.9, 803.0–804.9, 850.0–854.1	Inward transfers from another acute care hospital
Brown et al. (18)	2019	CDC-recommended ICD-10 codes^¶	NR
Chan et al. (43)	2005	2–18 yr; Isolated closed HI, mechanism witnessed & reported to police, HI symptoms, initial GCS ≥ 13 improving to 15, no abnormal or focal finding on neurological examination within 24 h of injury	History of bleeding diatheses or neurological disorders; multiple trauma; intentional head trauma; speech disturbances; altered mental status before incident
Chapital et al. (20)	2007	ICD-9-CM 800.0–801.9, 803.0–804.9, 850.0–854.1, 959.01	Second admission during study period
Cheng et al. (27)	2017	CDC-recommended ICD-10 codes^¶	NR
Cheng et al. (45)	2020	0–19 yr; CDC-recommended ICD-10 codes^¶	NR
Chiang et al. (46)	2006	13–18 yr, CT-diagnosed HI	NR
Chiu et al. (19)	2007	Concussion, skull fracture, neurological & cognitive deficit, PTA, neurological sequelae, ICH	NR
Daugherty et al. (28)	2021	CDC-recommended ICD-10 codes^¶	NR
Feigin et al. (38)	2013	WHO criteria: acute brain injury resulting from mechanical energy to head from external physical forces. Presence of 1/more of: confusion/disorientation, LOC, PTA, other neurological abnormalities	NR
Gabella et al. (15)	1997	Colorado resident; injury occurred in Colorado; ICD-9-CM 800.0–801.9, 803.0–804.9, 850.0–854.1	Brain injuries resulting from a disease process or decreased O2 supply to brain
Gontkovsky et al. (29)	2006	≥16 yr; in-patient rehabilitation patients with medically-documented TBI admitted to NIDRR TBI Model System center within 72 h discharge from acute care; treatment at Level 1 trauma center within 24 h injury	Not contactable to 1-yr follow-up; missing data; residing out of state or in jail at follow-up; history of major neurological deficit prior to sustaining TBI
Graves et al. (30)	2019	<18 yr; mTBI diagnosis; ICD-9-CM 800.0–801.9, 803.0–804.9, 850.0–854.1, 950.1–950.3, 995.55. Continuously enrolled for at least 180 days prior to and after index TBI diagnosis.	Cases missing region/MSA data; index TBI date coincident with a hospital admission (considered more severe injuries); cases with extremity AIS ≥ 3.
Halldorsson et al. (44)	2007	0–19 yr; ICD-9 850–854	NR
Harradine et al. (39)	2004	16–65 yr; >7 days PTA; de-novo TBI in previous 6 months; admitted to BIRP	No consent; previous TBI/acquired brain injury; past medical history likely to affect recovery
Harrison et al. (40)	2012	15–24 yr; received in-patient care at public & private hospitals; CDC-recommended ICD-10 codes^¶	NR
Johnstone et al. (31)	2003	Qualified for VR services based on primary/secondary TBI diagnosis	Did not complete VR service
Karwat et al^.† (11,49)	2009	Medically-diagnosed HI; hospitalized > 1 day	NR
Leonhard et al. (32)	2015	0–19 yr; ICD-9-CM^§ +959.01; meets prehospital triage criteria, or requires surgeon’s evaluation or treatment or activation of trauma team, or requires transfer to a trauma center, or ISS > 8, death, major operative procedure to head/chest/abdomen within 6 h or admitted to ICU within 24 h	Out-of-state location of injury; non-trauma hospitals; no transfer to trauma center made; prehospital death
Maier et al. (17)	2014	Hospitalized with CT-confirmed TBI diagnosis	Cranial CT scanning performed for research purposes concerning epilepsy & neurocysticercosis.
Ponsford et al. (6)	2012	In-patient at Epworth Rehabilitation Centre; participated in 2-yr follow-up	Residing interstate or overseas
Pozzato et al. (21)	2019	NSW resident; 1st hospital admission of TBI; CDC-recommended ICD-10 codes (S01.0-S07.1 only)^¶	Non-residents of NSW; non-acute episodes of care; subsequent admissions
Ratliff et al. (33)	2021	CDC-recommended ICD-10 codes^¶	Counties with 20 or fewer TBI deaths
Reid et al. (34)	2001	0–19 yr; Minnesota resident; TBI resulting in hospitalization/death; ICD-9-CM codes 800.0–801.9, 803.0–804.9, 850.0–854.1, 873.0–873.9	NR
Ring et al. (41)	1986	Neurotrauma patients hospitalized in NSW with EDH, ASDH, CSDH, or other HI leading to death; ICD-8 851–3 or 800–804, 850 or 854 and operation code 1–19, 84 or 888 or 430–438	Hospitals outside the boundaries of NSW
Robertson & McConnel (35)	2011	0–18 yr; severe TBI; ICD-9 800, 801, 802, 804, 850–854, 959.01	Injury not accidental (abuse, assault, or injury through other purposeful means)
Schootman & Fuortes (36)	2000	ICD-9-CM 800–801, 803–804, 850–854	NR
Simpson et al. (42)	2016	18–65 yr; severe TBI; active client of BIRP (3 occasions of service during 6-month period)	Paediatric BIRP services
Stewart et al. (37)	2014	<18 yr; concussion; ICD-10-CA S06 & R40.29, R41.1–3, R41.8, S00-T98	Penetrating HI; return visits for reevaluation of same concussion
Tesfaw et al. (47)	2021	>18 yr; systematic random sampling of trauma patients admitted to DTTRH ED	NR
Woodward et al. (22)	1984	Hospitalised; ICD-9-CM 800.0–804.9, 850.0–854.9	Direct admissions from another hospital
Yates et al. (48)	2006	NHS Centre for Clinical Coding and Classification codes 18, 19	NR

^†Karwat et al. (2009A and 2009B) report different outcomes on the same patient population, and are therefore considered as one study. ^¶ S01.0-S01.9, S02.0, S02.1, S02.3, S02.7-S02.9, S04.0, S06.0-S06.9, S07.0, S07.1, S07.8, S07.9, S09.7-S09.9, T01.0, T02.0, T04.0, T06.0, T90.1, T90.2, T90.4, T90.5, T90.8, T90.9; ^§ Barell et al. (65). NR, none reported; ICD, International Classification of Diseases; TBI, traumatic brain injury; CM, Clinical Modification; ED, emergency department; CDC, Centers for Disease Control and Prevention; HI, head injury; CT, computed tomography; PTA, post-traumatic amnesia; ICH, intracranial hemorrhage; WHO, World Health Organization; LOC, loss of consciousness; NIDRR, National Institute in Disability and Rehabilitation Research; mTBI, mild traumatic brain injury; MSA, Metropolitan Statistical Area; AIS, Abbreviated Injury Score; BIRP, Brain Injury Rehabilitation Program; VR, Vocational Rehabilitation; ISS, Injury Severity Score; ICU, intensive care unit; NSW, New South Wales; EDH, extradural hematoma; ASDH, acute and subacute subdural hematoma; CSDH, chronic subdural hematoma; CA, Canada; DTTRH, Debre Tabor Teaching and Referral Hospital; NHS, National Health Service.

Table

Author	Year	Data Source(s)
Agrawal et al. (14)	2017	Not defined
Andelic et al. (16)	2012	Rural = Northern & Central regions; Urban = Western and Southern regions
Asemota et al. (26)	2013	Not defined
Berry et al. (5)	2010	ABS ASGC: Rural = inner regional, outer regional, remote, very remote; Urban = major city
Brown et al. (18)	2019	US Department of Agriculture UIC: Rural = ≥3; Urban = ≤2
Chan et al. (43)	2005	Rural = Kota Bharu,;Urban = Ipoh
Chapital et al. (20)	2007	US Census criteria: Rural = jurisdictions outside Honolulu County; Urban = Honolulu County
Cheng et al. (27)	2017	Chinese CDC DSP: Rural = county; Urban = district
Cheng et al. (45)	2020	US CDC NCHS Urban-Rural Classification Scheme: Rural = rural area; Urban = large city and suburbs or medium or small city
Chiang et al. (46)	2006	Rural = Hualian County; Urban = Taipei
Chiu et al. (19)	2007	Rural = Hualian County; Urban = Taipei
Daugherty et al. (28)	2021	US Census Bureau: Rural = all non-urban population, housing, and territory; Urban = at least 2500 persons, at least 1500 live outside institutional group quarters
Feigin et al. (38)	2013	Rural = Hamilton, Urban = Waikato District
Gabella et al. (15)	1997	US Census Bureau: Rural = adjacent to MSA county or population of 2500, or not adjacent to MSA with population < 2500; Urban = MSA or CMSA
Gontkovsky et al. (29)	2006	Goodall et al. (63): Urbanicity scores calculated based on populations of 3 largest cities in each county. Higher urbanicity scores = more urban (less rural) county
Graves et al. (30)	2019	US Census Bureau: Rural = county with no MSA coding; Urban = MSA (metropolitan or micropolitan)
Halldorsson et al. (44)	2007	Rural = rest of Iceland; Urban = Reykjavik
Harradine et al. (39)	2004	ARIA RRMA: Rural = 3–7; Urban = 1–2
Harrison et al. (40)	2012	ABS ASGC: Rural = inner regional, outer regional, remote, very remote; Urban = major city
Johnstone et al. (31)	2003	US OMB: Rural = non-metropolitan; Urban = metropolitan
Karwat et al. (11,49)	2009	Not defined
Leonhard et al. (32)	2015	US CDC NCHS Urban-Rural Classification Scheme: Rural = rural area; Urban = large city and suburbs or medium or small city
Maier et al. (17)	2014	Rural = Haydom Lutheran Hospital; Urban = Aga Khan Hospital
Ponsford et al. (6)	2012	Rural = Regional Victoria (>25 km from central business district); Urban = Metropolitan Melbourne
Pozzato et al. (21)	2019	ABS ASGC: Rural = inner regional, outer regional, remote, very remote; Urban = major city
Ratliff et al. (33)	2021	US Department of Agriculture Rural-Urban Continuum Codes: Rural = 4–9; Urban = 1–3
Reid et al. (34)	2001	Goldsmith et al. (64): Rural = non-metropolitan and parts of large metropolitan counties without easy geographical access to central areas; Urban = metropolitan
Ring et al. (41)	1986	Rural = country base or small hospital; Urban = teaching and metropolitan surgical hospital or other private hospital
Robertson & McConnel (35)	2011	US Department of Agriculture RUCA2: Rural = small and isolated towns; Urban = urban and large towns
Schootman & Fuortes (36)	2000	US Census Bureau: Rural = county with no MSA coding; Urban = MSA (metropolitan or micropolitan)
Simpson et al. (42)	2016	ABS ASGC: Rural = inner regional, outer regional, remote, very remote; Urban = major city
Stewart et al. (37)	2014	Statistics Canada DA: Rural = non-urban DA; Urban = minimum population concentration of > 1000 people & population density > 400 people/km^2
Tesfaw et al. (47)	2021	Not defined
Woodward et al. (22)	1984	ABS: Rural = outside Adelaide Statistical Division; Urban = within Adelaide Statistical Division
Yates et al. (48)	2006	Not defined

† Karwat et al. (2009A and 2009B) report different outcomes on the same patient population, and are therefore considered as one study. ABS, Australian Bureau of Statistics; ASGC, Australian Standard Geographical Classification; US = United States; UIC, Urban Influence Code; CDC, Center for Disease Control and Prevention; DSP, Disease Surveillance Point; NCHS, National Center for Health Statistics; MSA, Metropolitan Statistical Area; CMSA, Consolidated Metropolitan Statistical Area; ARIA, Accessibility/Remoteness Index of Australia; RRMA, Rural, Remote and Metropolitan; OMB, Office of Management and Budget; RUCA2, Rural and Urban Commuting Area 2; DA, Dissemination Area.

Gabella B, Hoffman RE, Marine WW, Stallones L. Urban and rural traumatic brain injuries in Colorado. Ann Epidemiol. 1997;7(3):207–12. doi: 10.1016/S1047-2797(96)00150-0.

 PubMed Web of Science ®Google Scholar

Andelic N, Anke A, Skandsen T, Sigurdardottir S, Sandhaug M, Ader T, Roe C. Incidence of hospital-admitted severe traumatic brain injury and in-hospital fatality in Norway: a national cohort study. Neuroepidemiology. 2012;38(4):259–67. doi: 10.1159/000338032.

 PubMed Web of Science ®Google Scholar

Asemota AO, George BP, Bowman SM, Haider AH, Schneider EB. Causes and trends in traumatic brain injury for United States adolescents. J Neurotrauma. 2013;30(2):67–75. doi: 10.1089/neu.2012.2605.

 PubMed Web of Science ®Google Scholar

Berry JG, Jamieson LM, Harrison JE. Head and traumatic brain injuries among Australian children, July 2000–June 2006. Inj Prevention. 2010;16(3):198–202. doi: 10.1136/ip.2009.022442.

 PubMed Web of Science ®Google Scholar

Brown JB, Kheng M, Carney NA, Rubiano AM, Puyana JC. Geographical disparity and traumatic brain injury in America: rural areas suffer poorer outcomes. J Neurosci Rural Pract. 2019;10(1):10–15. doi: 10.4103/jnrp.jnrp_310_18.

 PubMed Web of Science ®Google Scholar

Chan HC, Aasim WA, Abdullah NM, Naing NN, Abdullah JM, Saffari MH, Osman A. Characteristics and clinical predictors of minor head injury in children presenting to two Malaysian accident and emergency departments. Singapore Med J. 2005;46(5):219–23.

 PubMedGoogle Scholar

Chapital AD, Harrigan RC, Davis J, Easa D, Withy K, Yu M, Takanishi, DM. Traumatic brain injury: outcomes from rural and urban locations over a 5-year period (Part 1). Hawaii Med J. 2007;66(12):318–21.

 PubMedGoogle Scholar

Cheng P, Yin P, Ning P, Wang L, Cheng X, Liu Y, Schwebel DC, Liu J, Qi J, Hu G, et al. Trends in traumatic brain injury mortality in China, 2006–2013: A population-based longitudinal study. PLOS Med. 2017;14(7):e1002332. doi: 10.1371/journal.pmed.1002332.

 PubMed Web of Science ®Google Scholar

Cheng P, Li R, Schwebel DC, Zhu M, Hu G. Traumatic brain injury mortality among U.S. children and adolescents ages 0-19 years, 1999-2017. J Safety Res. 2020;72:93–100. doi: 10.1016/j.jsr.2019.12.013.

 PubMed Web of Science ®Google Scholar

Chiang M-F, Chiu W-T, Chao HJ, Chen W-L, Chu S-F, Chen S-J, Hung C-C, Tsai S-H. Head injuries in adolescents in Taiwan: a comparison between urban and rural groups. Surg Neurol. 2006;66:S14–9. doi: 10.1016/j.surneu.2006.08.029.

 PubMedGoogle Scholar

Chiu W-T, Huang S-J, Tsai S-H, Lin J-W, Tsai M-D, Lin T-J, Huanh WCW. The impact of time, legislation, and geography on the epidemiology of traumatic brain injury. J Clin Neurosci. 2007;14(10):930–35. doi: 10.1016/j.jocn.2006.08.004.

 PubMed Web of Science ®Google Scholar

Daugherty J, Zhou H, Sarmiento K, Waltzman D. Differences in state traumatic brain injury-related deaths, by principal mechanism of injury, intent, and percentage of population living in rural areas - United States, 2016-2018. MMWR Morb Mortal Wkly Rep. 2021;70(41):1447–52. doi: 10.15585/mmwr.mm7041a3.

 PubMed Web of Science ®Google Scholar

Feigin VL, Theadom A, Barker-Collo S, Starkey NJ, McPherson K, Kahan M, Dowell A, Brown P, Parag V, Kydd J, et al. Incidence of traumatic brain injury in New Zealand: a population-based study. Lancet Neurol. 2013;12(1):53–64. doi: 10.1016/S1474-4422(12)70262-4.

 PubMed Web of Science ®Google Scholar

Agrawal A, Munivenkatappa A, Rustagi N, Mohan P, Subrahmanyan BV. Epidemiological characteristics affecting outcome in traumatic brain injury. J Med Soc. 2017;31(1). doi: 10.4103/0972-4958.198435.

 Google Scholar

Gontkovsky ST, Sherer M, Nick TG, Nakase-Thompson R, Yablon SA. Effect of urbanicity of residence on TBI outcome at one year post-injury. Brain Inj. 2006;20(7):701–09. doi: 10.1080/02699050600744103.

 PubMed Web of Science ®Google Scholar

Graves JM, Mackelprang JL, Moore M, Abshire DA, Rivara FP, Jimenez N, Fuentes M, Vavilava MS. Rural-urban disparities in health care costs and health service utilization following pediatric mild traumatic brain injury. Health Serv Res. 2019;54(2):337–45. doi: 10.1111/1475-6773.13096.

 PubMed Web of Science ®Google Scholar

Halldorsson JG, Flekkoy KM, Gudmundsson KR, Arnkelsson GB, Arnarson EO. Urban-rural differences in pediatric traumatic head injuries: a prospective nationwide study. Neuropsychiatr Dis Treat. 2007;3(6):935–41. doi: 10.2147/NDT.S2034.

 PubMedGoogle Scholar

Harradine PG, Winstanley JB, Tate R, Cameron ID, Baguley IJ, Harris RD. Severe traumatic brain injury in New South Wales: comparable outcomes for rural and urban residents. Med J Aust. 2004;181(3):130–34. doi: 10.5694/j.1326-5377.2004.tb06202.x.

 PubMed Web of Science ®Google Scholar

Harrison JE, Berry JG, Jamieson LM. Head and traumatic brain injuries among Australian youth and young adults, July 2000-June 2006. Brain Inj. 2012;26(7–8):996–1004. doi: 10.3109/02699052.2012.660515.

 PubMed Web of Science ®Google Scholar

Johnstone B, Price T, Bounds T, Schopp LH, Schootman M, Schumate D. Rural/urban differences in vocational outcomes for state vocational rehabilitation clients with TBI. NeuroRehabilitation. 2003;18(3):197–203. doi: 10.3233/NRE-2003-18303.

 PubMed Web of Science ®Google Scholar

Karwat ID, Gorczyca R, Krupa S. Causes and consequences of head injuries among rural population hospitalized in the Ward for Multi-Organ Injuries. I. demographic and social structure. Ann Agric Environ Med. 2009;16(1):15–22.

 PubMed Web of Science ®Google Scholar

Karwat ID, Krupa S, Gorczyca R. Causes and consequences of head injuries among rural inhabitants hospitalised in a Multi-organ Injury Ward. II. circumstances, types and consequences of head injuries. Ann Agri Environ Med. 2009;16(1):23–29.

 PubMed Web of Science ®Google Scholar

Leonhard MJ, Wright DA, Fu R, Lehrfeld DP, Carlson KF. Urban/rural disparities in Oregon pediatric traumatic brain injury. Inj Epidemiol. 2015;2(1):32. doi: 10.1186/s40621-015-0063-2.

 PubMedGoogle Scholar

Maier D, Njoku I, Jr., Schmutzhard E, Dharsee J, Doppler M, Hartl R, Winkler AS. Traumatic brain injury in a rural and an urban Tanzanian hospital: a comparative, retrospective analysis based on computed tomography. World Neurosurg. 2014;81(3–4):478–82. doi: 10.1016/j.wneu.2013.08.014.

 PubMed Web of Science ®Google Scholar

Ponsford J, Olver J, Ponsford M, Schönberger M. Two-Year Outcome following traumatic brain injury and rehabilitation: a comparison of patients from metropolitan Melbourne and those residing in regional Victoria. Brain Impair. 2012;11(3):253–61. doi: 10.1375/brim.11.3.253.

 Web of Science ®Google Scholar

Pozzato I, Tate RL, Rosenkoetter U, Cameron ID. Epidemiology of hospitalised traumatic brain injury in the state of New South Wales, Australia: a population-based study. Aust N Z J Public Health. 2019;43(4):382–88. doi: 10.1111/1753-6405.12878.

 PubMed Web of Science ®Google Scholar

Ratliff H, Korst G, Moth J, Jupiter D. Geographical variation in traumatic brain injury mortality by proximity to the nearest neurosurgeon. J Surg Res. 2021;259:480–86. doi: 10.1016/j.jss.2020.09.004.

 PubMed Web of Science ®Google Scholar

Reid SR, Roesler JS, Gaichas AM, Tsai AK. The epidemiology of pediatric traumatic brain injury in Minnesota. Arch Pediatr Adolesc Med. 2001;155(7):784–89. doi: 10.1001/archpedi.155.7.784.

 PubMedGoogle Scholar

Ring IT, Berry G, Dan NG, Kwok B, Mandryk JA, North JB, Selecki BI, Sewell MF, Simpson DA, Stening WA, et al. Epidemiology and clinical outcomes of neurotrauma in New South Wales. Aust N Z J Surg. 1986;56(7):557–66. doi: 10.1111/j.1445-2197.1986.tb07099.x.

 PubMedGoogle Scholar

Robertson BD, McConnel CE. Town-level comparisons may be an effective alternative in comparing rural and urban differences: a look at accidental traumatic brain injuries in North Texas children. Rural Remote Health. 2011;11(1):1521. doi: 10.22605/RRH1521.

 PubMed Web of Science ®Google Scholar

Schootman M, Fuortes LJ. Ambulatory care for traumatic brain injuries in the US, 1995-1997. Brain Inj. 2000;14(4):373–81. doi: 10.1080/026990500120664.

 PubMed Web of Science ®Google Scholar

Simpson GK, Daher M, Hodgkinson A, Strettles B. Comparing the injury profile, service use, outcomes, and comorbidities of people with severe TBI across urban, regional, and remote populations in New South Wales: a multicentre study. J Head Trauma Rehabil. 2016;31(2):E26–38. doi: 10.1097/HTR.0000000000000160.

 PubMed Web of Science ®Google Scholar

Stewart TC, Gilliland J, Fraser DD. An epidemiologic profile of pediatric concussions: identifying urban and rural differences. J Trauma Acute Care Surg. 2014;76(3):736–42. doi: 10.1097/TA.0b013e3182aafdf5.

 PubMed Web of Science ®Google Scholar

Tesfaw A, Eshetu M, Teshome F, Fenta E, Gelaw M, Mihret G, Atiklt G, Yosef T. Prevalence of head injury among trauma patients at Debre Tabor comprehensive specialized hospital, north central ethiopia. Open Access Surg. 2021;14:47–54. doi: 10.2147/OAS.S321404.

 Web of Science ®Google Scholar

Woodward A, Dorsch MM, Simpson D. Head injuries in country and city. Med J Aust. 1984;141(1):13–17. doi: 10.5694/j.1326-5377.1984.tb132660.x.

 PubMed Web of Science ®Google Scholar

Yates PJ, Williams WH, Harris A, Round A, Jenkins R. An epidemiological study of head injuries in a UK population attending an emergency department. J Neurol Neurosurg Psychiatry. 2006;77(5):699–701. doi: 10.1136/jnnp.2005.081901.

 PubMed Web of Science ®Google Scholar

Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135. doi: 10.1186/1471-2288-14-135.

 PubMed Web of Science ®Google Scholar

Barell V, Aharonson-Daniel L, Fingerhut LA, Mackenzie EJ, Ziv A, Boyko V, Abargel A, Avitzour M, Heruti R. An introduction to the Barell body region by nature of injury diagnosis matrix. Inj Prev. 2002;8(2):91–96. doi: 10.1136/ip.8.2.91.

 PubMed Web of Science ®Google Scholar

Goodall CR, Kafadar K, Tukey JW. Computing and using rural versus urban measures in statistical applications. Am Stat. 1998;52(2):101–11. doi: 10.1080/00031305.1998.10480548.

 Web of Science ®Google Scholar

Goldsmith HF, Puskin D, Stiles DJ, editors. Improving the operational definition of “rural areas” for Federal programs. Rockville, MD: Federal Office of Rural Health Policy; 1997.

 Google Scholar

Data availability statement

This systematic review and meta-analysis is a synthesis of existing published data, openly available in cited references.