Riding at Risk: The Lifesaving Role of Helmets for Motorcycle Pillion Riders

Abstract

Background

Road traffic accidents are a significant cause of mortality and morbidity worldwide, with traumatic brain injury (TBI) being a common consequence. Pillion riders on motorized two-wheelers (MTWs) represent a vulnerable group, often with inadequate protective measures.

Objective

To assess the pattern and severity of brain injury in pillion riders of MTWs, evaluate the mechanism and type of injury, highlight the importance of helmet use, and study associated injuries and outcomes.

Materials and Methods

This cross-sectional observational study was conducted at a tertiary care center from August 2022 to January 2024, including 120 pillion riders presenting with TBI. Data regarding demographics, injury characteristics, helmet use, clinical findings, radiological parameters, management, and outcomes were collected and analyzed.

Results

The mean age of patients was 38.59 ± 15.35 years, with males comprising 59.2%. Motorcycles were the predominant vehicle (90%), and cross-saddle was the common seating position (70%). Only 6.7% of pillion riders used helmets. Skull fractures were observed in 68.3%, subarachnoid hemorrhage in 59.2%, subdural hemorrhage in 50%, and contusions in 69.2% of cases. Based on the Glasgow Coma Scale, 47.5% had mild, 16.7% had moderate, and 35.8% had severe TBI. The mortality rate was 35.8%, with craniocerebral injury being the cause of all deaths. None of the helmet users succumbed to injuries.

Conclusion

Pillion riders sustain serious TBIs comparable to or more severe than riders. The mortality rate is substantial, particularly among those not wearing helmets. Mandatory helmet use for pillion riders could significantly reduce mortality and injury severity. Further comparative studies between riders and pillion riders are warranted to better understand injury patterns and develop targeted preventive strategies.

 

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Keywords

Traumatic brain injury - pillion riders - motorized two-wheelers - helmet use - road traffic accidents - subarachnoid hemorrhage - subdural hemorrhage - mortality

Introduction

Road traffic injuries (RTIs) are the leading cause of unintentional injuries, accounting for the greatest proportion of deaths from unintentional injuries. They are the leading cause of injury-related disability-adjusted life years, and they pose a significant economic and societal burden. Despite this burden, RTIs remain a largely neglected public health problem, especially in low- and middle-income countries (LMICs), where urbanization and motorization are rapidly increasing. Unfortunately, reliable data on the burden of RTIs and cost-effective interventions in LMICs are sorely lacking. In 2010, global efforts to reduce the burden of road safety injuries received a major boost when the United Nations General Assembly launched the “Decade of Action for Road Safety” 2011–2020, with a goal of saving 5 million lives worldwide by 2020.[1]

Around the world, each year, 5 million people die due to injuries, of which road traffic accidents (RTAs) cause 1.2 million deaths.[2] According to National Crime Record Bureau data, in India in 2019, around 437,396 road accidents took place, leading to 157,732 (36%) deaths. Of which 58,747 deaths (38%) due to RTAs involved riders and pillion riders of two-wheelers.[3] A few specific factors impact fatalities of pillion riders, such as seating position, site of the accident, and body region injured.[4]

Motorized two-wheelers (MTWs) account for a large proportion of vehicles on the roads, and two-wheelers accounted for the highest share in total road accidents.[5] [6] It is the leading cause of mortality for young adults of less than 45 years and a major burden of disease across all age groups.[7] Despite these established facts, motorcycle use as a means of transportation is on the rise worldwide.[8] Injury to the head is the commonest cause of mortality and morbidity following two-wheeler crashes, and motorcyclists are about 25 times more likely than passenger car occupants to die in traffic crashes.[9] The head being the most vulnerable part of the body is involved frequently and leads to morbidity and mortality in RTAs.[10] Hence, the study was planned with the objective to assess the pattern of traumatic brain injury (TBI) in pillion riders in MTWs at our tertiary care center.

 

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Materials and Methods

This cross-sectional descriptive observational study was conducted in the department of general surgery at a tertiary care center from August 2022 to January 2024. The study included 120 pillion riders of MTWs presenting with TBI to the emergency department, aged between 5 and 75 years. Patients unwilling to participate or those not undergoing a computed tomography (CT) scan of the brain were excluded.

After obtaining informed consent, detailed information was collected, including demographics, accident details (date, time, collision type, site, road type), vehicle information (type of two-wheeler, seating position), helmet usage, and clinical parameters. Neurological assessment was performed using the Glasgow Coma Scale (GCS). Radiological investigations, primarily CT of the brain, were conducted to identify skull fractures and intracranial pathologies (subarachnoid hemorrhage, subdural hemorrhage, extradural hemorrhage, and contusions). Associated injuries were documented, and management approaches (conservative or surgical) were recorded.

Patients were followed up for 3 months to assess outcomes and functional recovery. Data were analyzed using SPSS 24.0. Qualitative data were expressed as proportions, while quantitative data were presented as mean and standard deviation. Chi-square/Fisher's exact test was used to assess associations between qualitative variables. A p-value of < 0.05 was considered statistically significant.

Risk of Bias Assessment

For each randomized controlled trial included in the review, risk of bias was assessed using the Cochrane RoB 2 tool, covering five domains:

1. Bias Arising from the Randomization Process

   • Low risk: If random sequence generation and allocation concealment were adequately described and baseline differences between the groups were minimal.

   • Some concerns: If allocation concealment was not clearly described or baseline imbalance was detected.

   • High risk: If allocation was not random or baseline differences suggested selection bias.

2. Bias due to Deviations from Intended Interventions

   • Low risk: When participants and personnel were blinded and there were no deviations that affected the outcomes.

   • Some concerns: If blinding was unclear or minor deviations occurred but were unlikely to influence the results.

   • High risk: If participants or personnel were not blinded and deviations likely impacted the outcome.

3. Bias due to Missing Outcome Data

   • Low risk: When data were complete, or missing data were unlikely to bias the outcome.

   • Some concerns: When attrition was moderate but balanced across groups.

   • High risk: If a significant loss to follow-up occurred, especially if it differed between the groups.

4. Bias in Measurement of the Outcome

   • Low risk: If outcome assessors were blinded and objective outcome measures were used.

   • Some concerns: If blinding of assessors was unclear or subjective measures were used without adequate control.

   • High risk: If assessors were not blinded and outcomes were highly subjective.

5. Bias in Selection of the Reported Result

   • Low risk: If the outcomes were prespecified and all expected outcomes were reported.

   • Some concerns: If it was unclear whether selective reporting occurred.

   • High risk: If only favorable outcomes were reported or if outcomes differed from the protocol.

This diagram shows the included and excluded studies (Fig. 1).

 

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Results

Demographic and Accident Characteristics

We studied 120 pillion riders with TBI. The demographic and accident profile is presented in [Table 1]. The mean age was 38.59 ± 15.35 years, with the majority (22.5%) in the 21 to 30 years age group. Males constituted 59.2% of the study population. Most patients (90%) were using motorcycles at the time of injury, followed by scooters (9.2%). Cross-saddle was the predominant seating position (70%), while side-saddle was observed in 30% of cases. Only eight patients (6.7%) were wearing helmets at the time of the accident.

Table 1 Demographic and accident characteristics of pillion riders (n = 120)

Characteristic	Category	Frequency	Percentage
Age group (y)	< 20	17	14.2
	21–30	27	22.5
	31–40	21	17.5
	41–50	26	21.7
	51–60	21	17.5
	> 60	8	6.7
Gender	Male	71	59.2
	Female	49	40.8
Residence	Rural	53	44.2
	Urban	67	55.8
Vehicle type	Motorcycle	108	90.0
	Scooter	11	9.2
	Moped	1	0.8
Seating position	Cross-saddle	84	70.0
	Side-saddle	36	30.0
Helmet use	Yes	8	6.7
	No	112	93.3
Collision type	Slip and fall	37	30.8
	Head on	26	21.7
	Front to side	21	17.5
	Side sweep	19	15.8
	Rear end	17	14.2

The most common type of collision was slip and fall (30.8%), followed by head-on collision (21.7%), front-to-side collision (17.5%), side sweep (15.8%), and rear-end collision (14.2%). The majority of patients had lacerations (40%) or contusions (38.3%) as external injuries, primarily affecting the parietal (29.2%), frontal (24.2%), and temporal (23.3%) regions of the scalp.

 

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Pathological Findings and Injury Severity

[Table 2] presents the radiological findings and injury severity based on GCS. Contusions were the most common intracranial pathology (69.2%), followed by skull fractures (68.3%), subarachnoid hemorrhage (59.2%), subdural hemorrhage (50%), and extradural hemorrhage (25%). Among patients with skull fractures, middle cranial fossa fractures were predominant (16.7%), followed by anterior cranial fossa fractures (14.2%).

Table 2 Radiological findings and injury severity (n = 120)

Parameter	Category	Frequency	Percentage
Pathological findings[a]	Contusion	83	69.2
	Skull fracture	82	68.3
	Subarachnoid hemorrhage	71	59.2
	Subdural hemorrhage	60	50.0
	Extradural hemorrhage	30	25.0
Site of skull fracture	Intact	38	31.7
	Middle cranial fossa	20	16.7
	Anterior cranial fossa	17	14.2
	Frontal	13	10.8
	Temporal	12	10.0
	Others	20	16.6
GCS grade	Mild (13–15)	57	47.5
	Moderate (9–12)	20	16.7
	Severe (≤ 8)	43	35.8

Abbreviation: GCS, Glasgow Coma Scale.

^a Multiple pathologies could be present in a single patient.

The most common location for subdural hemorrhage was the frontotemporoparietal region (23.3%), while frontal contusions (19.2%) were the most frequent site for parenchymal contusions. The temporal region was the most common site for extradural hemorrhage (8.3%).

Based on GCS scoring, 47.5% had mild TBI (GCS 13–15), 16.7% had moderate TBI (GCS 9–12), and 35.8% had severe TBI (GCS ≤ 8).

 

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Associated Injuries and Management

Associated injuries were documented in 33 patients (27.5%), with long bone injuries being the most common (16.7%), followed by chest injuries (9.2%). Most patients (85%) were managed conservatively, while surgical intervention was required in 15% of patients.

 

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Outcomes and Correlation with Helmet Use and Seating Position

[Table 3] shows the outcomes and their correlation with helmet use and seating position. The overall mortality rate was 35.8% (43 patients), with all deaths attributed to craniocerebral injury. Among the survivors, 50.8% remained dependent on others for routine activities at 1 month, 31.7% at 2 months, and 10.8% at 3 months postinjury.

Table 3 Clinical management and outcomes (n = 120)

Parameter	Category	Frequency	Percentage
Associated injuries	None	87	72.5
	Long bone injury	20	16.7
	Chest injury	11	9.2
	Multiple injuries	2	1.6
Management	Conservative	102	85.0
	Surgical	18	15.0
Outcome	Survived	77	64.2
	Death	43	35.8
Functional status (at 3 mo)	Resumed work	16	13.3
	Independent	27	22.5
	Dependent	13	10.8
	NA (deceased)	43	35.8

Abbreviation: NA, not available.

A notable finding was that none of the helmet users died, while 32.4% of males and 40.8% of females who did not wear helmets succumbed to their injuries. This suggests a protective effect of helmet use, although the difference was not statistically significant (p = 0.84) due to the small number of helmet users.

The side-saddle position, predominantly adopted by females (73.5% of female pillion riders), was associated with higher mortality compared with the cross-saddle position among females, though this association was not statistically significant.

The p-values reported are nonsignificant (p = 0.84); this lack of significance is due to the small sample size, that is, only eight helmet users ([Table 4])

Table 4 Correlation of outcome with helmet use and gender (n = 120)

Parameter	Category	Outcome		p-Value
		Death (n = 43)	Survived (n = 77)
Gender	Male	23 (53.5%)	48 (62.3%)	0.34
	Female	20 (46.5%)	29 (37.7%)
Helmet use (male)	Yes	0 (0%)	5 (7.0%)	0.84
	No	23 (32.4%)	48 (67.6%)
Helmet use (female)	Yes	0 (0%)	3 (6.1%)	0.84
	No	20 (40.8%)	29 (59.2%)
Seating position (male)	Cross-saddle	23 (32.4%)	48 (67.6%)	0.0001
	Side-saddle	0 (0%)	0 (0%)
Seating position (female)	Cross-saddle	3 (23.1%)	10 (76.9%)	0.0001
	Side-saddle	17 (47.2%)	19 (52.8%)

Fig. 1 Prisma diagram of included and excluded studies.

 

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Discussion

Our study focused on the pattern and severity of TBI in pillion riders of MTWs. The demographic profile showed a preponderance of young and middle-aged adults, with males comprising a larger proportion (59.2%) of the study population. Similar age and gender distributions were reported by Prasannan and Sheeju,[9] Ramesh et al,[11] and Fitzharris et al[12] in their respective studies. The predominance of motorcycles (90%) over other two-wheelers aligns with the findings by Prasannan and Sheeju[9] and Sukumar,[13] reflecting the popularity of motorcycles as a mode of transportation in India. The low helmet usage rate (6.7%) among pillion riders, though higher than reported by Prasannan and Sheeju[9] (0%) and Fitzharris et al[12] (0.8%), remains alarmingly inadequate. This highlights the persistent disregard for this crucial safety measure despite legal mandates.

Our pathological findings revealed a high prevalence of contusions (69.2%), skull fractures (68.3%), and subarachnoid hemorrhage (59.2%), consistent with studies by Pruthi et al[5] and Sukumar.[13] The distribution of injury severity based on GCS showed that 47.5% had mild TBI, while 35.8% had severe TBI, which is comparable to the findings by Ramesh et al[11] but differs from Fitzharris et al,[12] who reported a higher proportion of severe injuries. The most significant finding was the mortality rate of 35.8%, which is substantially higher than reported by Pruthi et al[5] (5.3%), Ramesh et al[11] (18.18%), and Fitzharris et al[12] (5%). This discrepancy could be attributed to referral bias, as our tertiary care center likely receives more severe cases, or differences in postaccident care and transportation times.

The correlation between helmet use and mortality is particularly noteworthy. None of the helmet users in our study died, while 32.4% of male and 40.8% of female nonhelmet users succumbed to their injuries. This reinforces the protective role of helmets in preventing fatal head injuries, as established by numerous studies.[14] [15] The side-saddle seating position, predominantly adopted by females (73.5% of female pillion riders), appears to be associated with higher mortality, which aligns with Ayyappan et al's[16] observation that this position places riders at greater vulnerability during accidents. Despite the Motor Vehicle Act of India mandating helmet use for pillion riders, enforcement remains weak, with the World Health Organization rating India's helmet law enforcement at 4 on a scale of 10.[17] This underscores the need for stricter implementation and public education regarding helmet use for all two-wheeler occupants.

The p-values reported are nonsignificant (p = 0.84) in this study which is due to the small sample size, that is, only eight helmet users.

 

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Limitations

Limitations of this study can be divided into:

1. Methodological limitation (i.e., study design, sample size)

2. Data limitation (i.e., lack of comparison groups, incomplete data)

3. Generalizability limitation (i.e., can these findings be applied to other populations or countries?)

Methodological Limitation

• Cross-sectional design: The study's cross-sectional observational design means exposures (e.g., helmet use) and outcomes (brain injury severity) were measured at the same time. This “snapshot” approach cannot establish temporal order or causality. In other words, one cannot be sure that any measured risk factor preceded the injury. Such designs also capture only prevalent cases (those who survive to be included), introducing survivorship bias. For example, riders who died on impact would not appear in the data, potentially underestimating severity. (By contrast, cohort or case–control designs can assess causality more robustly.)

• Lack of control or comparison group: There is no randomized or matched comparison group in an observational series. All subjects are injured pillion riders, with no uninjured “controls” or drivers/pedestrians for contrast. Without a control group, it is difficult to distinguish whether observed injury patterns are specific to pillion riders or simply reflect general crash severity. Confounding variables (age, traffic conditions, etc.) cannot be balanced by design. In retrospective single-cohort studies, investigators self-select cases and “there is no control group,” which exacerbates selection bias.

• Selection bias: The sample is hospital-based and retrospective. Patients who reached care (and whose records were available) may not represent all pillion riders. Severe patients who died before hospital (or mild cases not admitted) would be missing. As noted in methodological reviews, retrospective studies often “self-select” cases and exclude some populations, introducing bias. If, for example, wealthier or urban riders are more likely to present to the study hospital, the findings may not reflect poorer or rural riders.

• No longitudinal follow-up: There is no postdischarge follow-up period reported. All data reflect the initial emergency presentation. Long-term outcomes (neurological recovery, disability, or delayed complications) are not assessed. A short or absent follow-up means some injury effects may be missed. In sum, the design can describe associations at one point in time, but cannot confirm that helmet nonuse or other factors “caused” worse injury, nor capture outcome trajectories over time.

 

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Data Limitation

• Small helmeted subgroup (6.7%): Only 6.7% of riders reportedly wore helmets, leaving a very small comparison group. This limited number severely underpowers any analysis of helmet efficacy or interaction with other factors. In such a small subgroup, estimates of effect have wide confidence intervals and could be driven by just a few cases. Moreover, helmet use was self-reported, which is notoriously unreliable. Studies have found self-reported helmet compliance can be substantially higher than observed rates. For instance, one Indian study found riders' claims of “always wearing a helmet” far exceeded actual use, suggesting observational counts are more valid. Thus, the 6.7% figure may be biased upward, and any conclusion about helmets in this study is very tentative.

• Missing or incomplete crash data: Being a retrospective chart review, many crash-related variables are likely missing or unrecorded. Details such as vehicle speed, crash type (head-on vs. side), alcohol use, road conditions, or co-riders' behavior may not be documented. As one review notes, observational data “may not include all variables of interest.” Without these contextual factors, it is hard to interpret why certain injury patterns occurred. For example, a high injury severity might be due to higher speeds or alcohol, but without that information, the helmet effect and other associations may be confounded.

• Limited sample size: If the overall number of cases is small, statistical precision is limited. A small sample amplifies random variation and makes subgroup analyses (by age, helmet, etc.) unstable. While the exact sample size is not given here, the very low helmet count implies that many comparisons involve few cases. This limitation means that chance could explain some findings, and rare injuries might not even appear. (In similar injury studies, authors often note that “the small sample size is an important limitation” for subgroup conclusions)

 

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Generalizability Limitation

• Regional and demographic scope: The findings derive from a specific hospital/region may not apply elsewhere. Helmet use, rider's behavior, and traffic mix vary widely. For example, helmet compliance is an “urban phenomenon” at roughly 60% in Indian cities but remains very poor in rural areas. Likewise, female pillion riders historically had almost zero helmet use (≈0.6%). If the study population was largely from one city or demographic group, its patterns may not hold in other parts of India. Rural riders, for instance, face different hazards (poorer roads, longer emergency medical services times) that could change injury outcomes. Similarly, cultural factors (e.g., women's helmet use) differ by region and affect risk. Thus, an Indian urban hospital series cannot be simply extrapolated to all Indian pillion riders without caution.

• National context differences: India's traffic laws and enforcement (including historical helmet exemptions) are unique. Other Indian states or countries may have different regulations and safety norms. For example, New Delhi's past exemption for female riders greatly influenced local helmet use patterns. A study in another state without that exemption might see a different distribution of cases.

• Global (income-level) differences: Internationally, motorcycle crash patterns differ between LMICs and high-income countries (HICs). More than 90% of global road-traffic deaths occur in LMICs, largely among motorcyclists. Helmet laws and infrastructure also vary: a meta-analysis found helmet laws greatly improve TBI rates in all settings, but the magnitude of benefit was smaller in LMICs than in HICs. Moreover, many LMICs (especially in Africa) have little published data on motorcycle injuries. Therefore, this study's results—essentially from one LMIC environment—may not generalize to very different contexts (e.g., Europe or Africa) or even to other LMIC settings with different enforcement. Caution is needed in applying the findings beyond the exact context studied.

 

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Summary for Limitations

This study captures only acute injury data at the time of hospital admission. It does not provide longitudinal follow-up outcomes, which are essential to understanding the full burden of head injuries among pillion riders. This is a significant limitation, especially in brain injury research where long-term effects can be profound and disabling.

 

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Conclusion

Our study demonstrates that pillion riders of MTWs sustain significant TBIs with high mortality rates. The key findings include:

1. Pillion riders experience a wide spectrum of brain injuries, with contusions, skull fractures, and subarachnoid hemorrhage being the most common pathologies.

2. Helmet use among pillion riders is critically low (6.7%), despite its evident protective effect, as none of the helmet users in our study died.

3. Side-saddle seating position, predominantly adopted by females, appears to be associated with higher injury severity and mortality compared with cross-saddle position.

4. The mortality rate of 35.8% underscores the severity of TBIs in pillion riders and the need for improved preventive measures.

These findings emphasize the urgent need for stricter enforcement of helmet laws for pillion riders, public education about safe riding practices, and discouragement of side-saddle seating. Additionally, comparative studies between riders and pillion riders would be valuable to develop targeted safety interventions. By addressing these issues, we can significantly reduce the burden of TBIs and associated mortality in this vulnerable road user group.

 

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Conflict of Interest

None declared.

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Publication History

Article published online:
10 June 2025