Artigos

Introduction
In the latest global road safety report, it is estimated that more than 1.35 million people die annually from road traffic injuries. In addition, these events are the leading cause of death in the 5?29-year-old age group1.
Literature reports multiple factors that increase the risk and effects of road crashes, such as excessive speed, driving or walking under the influence of alcohol, the non-use of seat belts, failure to post road signs, the non-use or improper use of helmets, poorly designed or deteriorated road infrastructure, and driving in unauthorized locations, among others2. It has been shown that road injuries are preventable because they occur due to factors related to human error, roads in inadequate states, weather conditions, and other predictable factors. Since 1960 in high-income countries, the adoption of strategies at the legislative level related to infrastructure, risk-prevention behaviours, speed control, use of belts, helmets, and lights by motorcyclists, and pedestrian crossings, among others, contributed to significant reductions in the incidence of these events and their impact on their populations3.
Most road traffic injuries are preventable by means of effective interventions such as designing safer infrastructure; improving vehicle safety features; improving post-incident victim care; and educating roadway stakeholders, such as establishing and enforcing laws related to key risk factors. A speed of 80 km/h exposes a pedestrian hit by a car to a 60% risk of death, driving under the influence of alcohol greatly increases the risk of being involved in a road incident when the blood alcohol level exceeds 0.04 g/dl; wearing a helmet or seat belt reduces the risk of death by 40%, and cell phone use has also been shown to increase the probability of a road accident by four times4.
Every year, 1.35 million people die on the roads, with the most affected being low- and middle-income countries —including Colombia— with an inequitable distribution since 80% of road traffic deaths and injuries occur in these countries, even though they have only half of the world's registered vehicles1. It is estimated that in these countries, road events cost between 1% and 3% of GDP5, which is more than the resources received to help improve the well-being of their populations. The United Nations, in the Sustainable Development Agenda 2030, has set an ambitious goal for road safety: to reduce the global number of road deaths and injuries by half6; however, it is clear that the Decade of Action for Road Safety also had this goal, which clearly was not met in most countries1.
In turn, the Colombian National Plan for Road Safety 2011?2021-PNSV aims to reduce the number of fatalities by 26% at the national level by 20217. On the contrary, in Colombia in 2010 the Road Traffic age-adjusted Mortality rates (RTM) were 12.5/100,000 inhabitants, increasing to 14.9 in 20168. In 2015, life expectancy at birth in Colombia was 71 years for men and 77 years for women9. Nonetheless, RTM reduces the life expectancy of Colombians because, for every 1,000 inhabitants in Colombia between 20 and 24 years of age, 10.2 years are lost, which is considered a public health problem and represents an economic impact in terms of social productivity10.
In last years, in Colombia between 20-21 people die every day from RTM8 with an annual average of around 7,500 deaths, making it the eighth cause of total mortality9 and the second cause of violent death in the country7. Additionally, RTM has grown rapidly over the past 25 years, increasing 7.2 times over the 1990 figure. The partial results of a study on the Decade of Action for Road Safety (2010-2015) showed that approximately 50% of fatal injuries occurred on motorcycles, 28% involved pedestrians, 5% occurred on bicycles, and approximately 10% involved car occupants11.
It is estimated that, by 2040, the number of motorcycles and cars in the country will have tripled12. In Colombia, 80% of fatal road traffic injuries involve men in the 15?29-year-old age group of the lower strata, and urban residential areas are the most affected population groups; 85% of the people who die from road traffic injuries in Colombia have at most a secondary education8, which is a determinant of road safety that is commonly ignored. In Medellín, the country's second-largest city, 80% of road deaths occurred among pedestrians, 70% of whom were over 50 years of age. Motorcycle injuries were the second injury road fatality cause, with 41.6% of deaths among those younger13. Results with similar implications were found in Bogota, the capital of the country14, and in the whole Colombian setting15. Motorcycles are the most commonly used transportation vehicle among those with lower education and socioeconomic strata16.
Although previous studies in Colombia have addressed the issue of risk factors for road incidents in a cross-sectional manner, focusing primarily on demographic characteristics, few studies consistently address inequalities in RTM. In general, health inequalities refer to ‘differences that are unnecessary and avoidable but also considered arbitrary and unfair’ that typically impact the health of the most vulnerable population groups17.
This study aims to provide a complementary vision by analysing educational inequalities in adults due to road mortality in Colombia, understood as a determinant of road safety, to improve the understanding of RTM in Colombia and provide inputs to understand this problem, as well as contributing with evidence to stakeholders to address the enormous social burden that these events imply for the country. The novelty of this research lies in its focus on educational disparities —a dimension frequently overlooked in previous studies— and its contribution to broadening the conceptualization of risk factors in road safety. Furthermore, it provides empirical evidence to inform the design of targeted public health interventions and policies aimed at reducing the substantial social and economic burden that RTM imposes on the country.

Materials and methods
This study is based on a population-level dataset provided by the Colombian National Administrative Department of Statistics (DANE), encompassing all officially registered deaths due to road traffic injuries over an 18-year period (1998–2015). Therefore, it is not based on a convenience sample but reflects the entire adult population of Colombia, ensuring comprehensive national representativeness.
We used methods similar to previous studies18,19. This is an ecological, longitudinal, retrospective, and analytical study based on the official records of deaths by RTM of the National Administrative Department of Statistics (DANE) between 1998 and 2015, which collects and harmonizes data on deaths based on international guidelines9. The data are public and are downloaded as simple anonymized records. The vital statistics records contain individual records of all deaths that occur in Colombia, with information on their demographic characteristics (age, sex), as well as educational level, available from 1998. The cause of death codes for road injury in this work, according to the International Classification of Diseases (ICD 10, 2011), are V01, V05-V06, V09.1, V10-11, V15-V18, V19.3, V19.8, V80.0-V80.2, V80.6-V80.9, V81.2-V81.9, V82.2-V82.9, V87.9, V88.9, V89.1, V89.3, V90-V99, AND 85.9.
According to the WHO, a road traffic fatality is considered to be someone that dies in less than 30 days after the road traffic incident, but in Colombia a fatality is considered a victim of a road traffic accident if the cause is directly related to the incident, regardless of the number of days, according Law20.
Aggregate variables are handled, where age and sex data are approximately 98% complete, but the education level variable was found to have 43% of values missing, with the figure generally decreasing throughout the period. The lost cases were imputed following multiple imputation methods in the SAS statistical package to control for errors in the measurement and recording of the source. For this procedure, a wide set of demographic variables was used (age, sex, urban/rural residence area, municipality and department of residence, and marital status). Details of this imputation process are available in another publication21.
The educational level was divided according to the highest educational level achieved in primary, secondary, or tertiary. The latter covered all types of post-secondary education (technical, technological, and university). Only adults (over 25 years of age) were included, assuming that most people in that age group have usually completed the educational cycle. Age was reclassified into three groups: young (25?44 years), mature (45?64 years), and older adults (over 65 years).
The proportion of the population by educational level was obtained from the five-year Demographic Health Surveys22. To construct the denominators of the rates, the population projections offered by DANE were used by five-year groups and by sex, generating records from 1985 to 2020, and have been interpolated through the population census23.
The data on RTM deaths were then calculated and divided by educational level by five-year groups by the population totals to obtain the mortality rates from these events in adults (over 25 years of age). First, the mortality rates, standardized by age, educational level, sex, and year were calculated with the 1997 World Health Organization standard as a reference24.
Subsequently, Poisson regression models were implemented to calculate the Risk Ratio (RR) for mortality according to educational level, taking the highest educational level (tertiary) as a reference group. To assess changes in inequalities controlling for changes in the distribution of education and residential area, the Relative Index of Inequality (RII) was estimated, a widely used measure to examine trends in health inequalities. The RII can be interpreted as the ratio of the mortality rate of those with the lowest educational levels compared to those with the highest educational levels. More details on RII are available in other publications25.
Additionally, to identify patterns of change in RTM in adults, the public domain software Joinpoint Trend Analysis Software®26 was used, which has been applied in numerous investigations27. This software takes the trend data (in the case of the present study, the annual standardized rates in the adult population and the RII, both with their respective standard error) and adjusts to the simplest inflection-point model that the data allow using a Monte-Carlo permutation, accounting for the Annual Percentage Change (APC) with its statistical significance in the intervals between the inflection points.
In this study, secondary sources were used corresponding to deaths that are provided anonymously under the provisions of the Habeas Data Law by the National Department of Statistics (DANE), and the population counts in an aggregate form available to the public from DANE itself. It was classified as a risk-free investigation according to what is prescribed by Colombian regulations.

Results
Of the 48,898 deaths in Colombia due to injury road between 1998-2015 due to RTM 80% were among men, being young men (25–44 years old) 40.7% of the deceased. The number of deceased increased with age. Among women, 39% of the deceased were seniors (65 years and over) and the number decreases as age decreases (Table 1). The highest mortality rates were in the senior population (65 years old and more) among both men and women (46.3, and 15.1/100,000, respectively), and the mortality rate caused by traffic in adult men (25 years old and more) (RTM) (33.8/100,000 population) was 4.5 times higher than in women (7.5/100,000). (Table 2).
Figures 1 and 2 display the trends based on age-standardized mortality rates (ASMR) per 100,000 inhabitants, rather than absolute numbers of deaths, to account for population changes and provide a more accurate comparison over time. RTM had a marked annual reduction (CPA = 4.1% men and 5.5% women) in the period between 1998 and 2011, reaching minimum mortality rates of 26.7/100,000 (men) and 5.4/100,000 (women), in 2011 (Figure 1). As of that year, a significant and sustained increase in RTM began in both sexes. Figure 2 shows that the trends, in all age groups and by sex, show a sustained initial fall in RTM, significant in men for all age groups, with an annual increase in recent years, being greater in middle-aged men (APC=6.5%).
Regarding the differences by educational level, RTM is consistently higher among people with a primary education level, compared with a secondary education level and this with a tertiary education level, behaviour that is maintained by sex and age groups, which is reflected in the Risk Ratio (RR), taking those with tertiary studies as a reference (Table 1). For men with a primary educational level, the risk of death was 2.29 (95% CI: 2.27–2.31), for those with secondary education it was 1.81 (95% CI: 1.78–1.82), these RRs being lower for women. The only divergence is in senior women with secondary education who have lower mortality compared to women with post-secondary education.
The annual reduction in RTM in 1998–2015 was greater in those with tertiary education (9.5% in men and 13.5% in women) compared to other educational groups. At the beginning of the period, there was, unusually, higher RTM in women with a higher level of education, but throughout the period, the fall at the end makes mortality lower in this population group (Figure 3).
To better explain all these findings, Figure 4 is disaggregated by educational level and age groups. It is evidenced that the increase in RTM in recent years is only significant, and pronounced, in young men (25–44 years) with tertiary and secondary education. In mature men with primary education, groups condition the trend. The increase at the end of the RTM period in women (Figure 1) is slight and not significant by educational level and age group. On the other hand, the fall observed in RTM in the first years of the period continues to be significant, even if it is broken down by educational and age groups. It is always more pronounced in men and women with tertiary education in all age groups.
The Relative Index of Inequality (RII) was 2.54 (95% CI: 2.51–2.57) in men and 2.11 (95% CI: 2.08–2.15) in women (Table 1). The trends in Figure 5 show a strong and significant increase in the RII until 2013 (6.1% men and 4.9% women), with a subsequent fall that is only significant in men (10.6%) and coincides with the period of the total increase in RTM. Table 1 shows that, for the entire period, the RII increases significantly in men and women (5% per year for men and 4% for women) and in all age groups, this growth being greater in mature men and women (8% and 9%, respectively).

Discussion
This study examines educational inequalities according to the level of education achieved (primary, secondary, and tertiary in RTM in adult men and women) and by age group (young, mature, and senior) from 1998 to 2015.
As in other contexts, we found in Colombia a period of increase in the mortality rates caused by traffic in adults (RTM) since 2011, which, when ungrouped, was only significant in mature, senior men (65+ years) with primary education (45–64 years) who reached an educational level higher than primary. This may be related to several factors such as the weakness in the management processes within the country for the control and prevention of RTM (the elimination of an entity in charge of promoting road safety known in the country as the National Fund for Road Prevention between 2011 and 2012); the creation and operation only until 2015 of the National Road Safety Agency28, generating a leadership vacuum on this issue at the national level.
Furthermore, this issue disproportionately affects older and vulnerable populations with lower educational attainment. It is frequently associated with lower socioeconomic status and disproportionately impacts individuals who do not typically operate private motor vehicles. As other authors have noted, this is a multidimensional problem that may require an intersectional perspective to achieve a deeper comprehension of its determinants.
Our findings reveal a pattern of growing road traffic mortality inequalities that, although consistent with global evidence, present distinctive features in the Colombian context34. For instance, while international literature has documented diverging trends according to educational level in high-income countries, in Colombia the reversal of the decreasing mortality trend since 2011 disproportionately affected groups with intermediate educational attainment, particularly middle-aged men. This phenomenon suggests the influence of context-specific factors, such as the explosive growth of motorcycles as an affordable means of transportation among lower socioeconomic groups12-29, as well as gaps in institutional road safety governance 28,-32.”
“Moreover, although deficiencies in enforcement and infrastructure are global concerns, their impact in Colombia appears to be magnified by the country's unique socioeconomic stratification and urbanization patterns8-9. In this sense, our findings not only align with previous international evidence but also highlight the urgent need for context-sensitive public policies in LMICs.
In addition to the above, the increase in the number of vehicles that has occurred is mainly due to the explosive and exponential increase in motorcycles that have been in the country during the last years29; which, as described below, has been associated with the increase in RTM in recent years.
These results are partially in agreement with those found in a study carried out in Cali between 1993 and 1997, where nearly 90% of deaths in adults over 60 years of age were due to being run over, especially by private vehicles, followed by public transport35. However, this trend may have changed in recent years, where close to 40% of collision deaths are caused by motorcycle drivers, affecting road actors of different ages8.
Some studies have related educational level to the type of victim in RTM: in pedestrians, a study in Bogotá showed that knowledge of traffic regulations and educational level were related to RTM36; In Nigerian drivers, the highest number of injured had primary education as the highest level, if the deterioration of visual functions was added, the risk of occurrence of RTM increased37.
In the present study, the trends reveal a growing inequality in RTM in Colombia, which causes a large number of victims among those with a lower educational level. This is consistent with a study in Ethiopia, which reported that those whose educational level was classified as ‘can read and write’ had a 35.2 times greater chance of having a serious injury than those who attained a higher education level38. Similarly, the elderly population and men were the most affected groups. It also coincides with national or international research where the gender role has been involved in RTM, in such a way that men have mortality risks between five to six times higher than women39,40.
However, both global and local literature offer limited insights into the association between educational inequalities and RTM, as well as how to address it41, despite evidence that socioeconomic disparities are a key determinant of road safety. Research specifically exploring the relationship between traffic-related injuries, lower educational attainment, and elderly populations remains scarce. Nevertheless, Hijar et al. (2003) reported that victims of road traffic incidents frequently belonged to socioeconomically disadvantaged and educationally underserved populations30. Similarly, in the United States, studies have documented a divergence in mortality trends, with mortality rates decreasing among individuals with higher educational levels but increasing among those with lower educational attainment31. European studies have reported similar patterns, particularly among men, where lower educational levels were associated with a higher prevalence of injuries42..
Building upon these findings, the present study reveals that individuals with tertiary education benefited the most during the period of RTM decline among adults. However, paradoxically, this same group has also experienced a greater burden during the recent increase in RTM. Furthermore, the greater rise in injuries among elderly men with only primary education, and among middle-aged men who attained education beyond primary level, fails to provide clear policy guidance. These findings highlight the need to explore additional dimensions of these inequalities beyond age and educational differences, underscoring the complexity of addressing RTM disparities.
The results so far have shown that the local intervention measures that have been taken to improve road safety in Colombian cities have not always been effective8. The reasons are various and of a speculative nature, among which are the presence of legislation, but lack of compliance; problems with inspection processes; the absence of follow-up, comparative studies with outcome evaluations; the non-continuity of policies due to administrative changes, among others43–45. In addition, as demonstrated in this study, socioeconomic differences should be considered as a key determinant for road safety, therefore addressing these differences is a public policy priority.
The observed reversal in road traffic mortality (RTM) trends beginning in 2011 reflects a real increase in standardized mortality rates, particularly among men and vulnerable populations. Several contextual factors likely contributed to this shift. Firstly, the elimination of the National Fund for Road Prevention between 2011 and 2012 resulted in a temporary absence of national leadership in road safety initiatives28. Secondly, there was a substantial rise in motorcycle use, particularly among individuals from lower socioeconomic backgrounds, which is strongly associated with increased RTM risk12,29. Thirdly, enforcement of road safety regulations weakened during this period 32, and, possibly, deteriorations in road infrastructure maintenance. Finally, an expansion in urban mobility patterns without corresponding improvements in transportation safety measures may have further exacerbated exposure to road traffic risks. These combined factors help to explain the abrupt change in mortality trends identified in our analysis.

Limitations
Despite this study having several strengths, some risks and potential limitations must be considered. For example, mortality data come from records of these events, while data on the population distribution come from demographic projections. This can give rise to the so-called potential information bias, known as the numerator/denominator46 that can generate an overestimation of inequalities. Another limitation is that the data on population size come from demographic projections, which, as described, are not sufficiently up to date.
Another important limitation of the present study is the potential underreporting of deaths in some regions. Previous studies suggest that underreporting is particularly high in the poorest regions, for example, the average proportion of all registered deaths ranged from 25% in Chocó, one of the poorest regions, to 90% in Antioquia, one of the most prosperous regions47. After years of working intensively with these two databases, it can be ensured that they are progressively more reliable over time in terms of lower under-registration, better quality, and coverage of the data. The estimates of inequalities probably result in an underestimation for this cause since people with lower socioeconomic status are more likely to live in areas with higher rates of under-registration. It is also possible that inequalities have been underestimated, as underreporting has increased during the study period. The present results, therefore, may indicate potentially greater inequalities than those reported.
There may be an underestimation of inequalities since missing values due to registration errors or omissions tend to be more frequent in regions with a lower educational level. However, the process of imputing missing values of this variable, based on a wide set of variables available for the records, is expected to have minimized the potential information bias.

Conclusions
With the recent increase in RTM in Colombia, it is necessary to reiterate to decision-makers the high social cost and the fact that these events can be prevented. Experience suggests the need for a coordinating body with sufficient funding and a national plan with policies that incorporate intervention measures in road safety according to the characterization of road traffic injuries (RTI) in each city with measurable goals through indicators and continuity regardless of administrative changes, which become crucial components of a sustainable response to the problem of road safety.
It is also necessary to focus public policies on population groups with different socioeconomic levels, since, according to previous evidence, they are differentially affected by drastic reductions in life expectancy. In addition, the consequences of the use of risky means of transportation among those disfavoured must be considered, emphasizing in the development of adequate road infrastructure to improve security for vulnerable population. Increasing and improving public transportation could also a good strategy to reduce the use of motorcycles.
To summarize, the multifaceted nature of road traffic injuries (RTIs) demands an interdisciplinary, intersectoral, and multilevel approach for successful intervention. Consequently, a coordinated effort involving Health, Transport, Education, Culture, Infrastructure, and Planning sectors, amongst others, is crucial to integrate resources, plans, and programs and prevent duplication of efforts.?
Statements

Contributions to the research
Nombre del autor CRediT (Contributor Roles Taxonomy
Iván Arroyave Conceptualization; Data curation; Formal analysis – statistical techniques, data analysis; Methodology – design and development; Supervision and leadership in planning; Writing – review & editing
Jorge-Martín Rodríguez Hernández Writing – original draft; Writing – review & editing
Yamileth Ortiz Gómez Writing – original draft; Writing – review & editing

Conflict of interest statements
We are pleased to report no conflict of interest by any of the authors of this paper.

Funding disclosure
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. There is no financial support for this work that could have influenced its outcome.

Data sharing statement:
Mortality databases and population estimations are publicly available in the webpage of the Colombian Administrative Agency of Statistics (DANE by the acronym in Spanish): www.dane.gov.co ?
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