Non-Fatal Work-Related Road Traffic Injuries During the Work Shift in Ecuador: A Descriptive Study of Social Security-Affiliated Workers

2.1 Study design and data source

A retrospective, nationwide, registry-based cross-sectional study was conducted using certified occupational accident records from Ecuador. The reporting of the study followed the STROBE statement [15] and the RECORD extension for studies based on routinely collected health data [16]. Data were obtained from an anonymized administrative database provided by the General Directorate of Occupational Risks (GDOR) of the Ecuadorian Social Security Institute (IESS). The database included all certified occupational accidents recorded between January 1, 2023, and December 31, 2024, and validated in accordance with national social security regulations [13].

2.2 Identification and selection of work-related travel accidents

The analysis was restricted to certified occupational accidents classified in the GDOR-IESS registry as occurring during the work shift (in-mission), while commuting accidents (in itinere) were excluded. Within this subset of certified in-mission occupational accidents, road traffic injuries were identified using ICD-10 external cause codes V01–V99 [17]. Thus, the classification of an event as in-mission was based on the occupational accident certification process recorded in the administrative database, whereas ICD-10 coding was used to identify the road traffic nature of the injury. The database did not allow further disaggregation into specific crash subtypes, such as pedestrians, motorcyclists, or vehicle occupants. However, it did include information on the nature and anatomical location of injuries, which enabled clinical characterization of the cases. The final analytic dataset comprised 2,363 certified non-fatal in-mission occupational road traffic injuries.

2.3 Study population

The study population comprised workers affiliated with the GDOR of the IESS. By the end of 2024, this population included approximately 3.29 million workers, representing 38.7% of the Economically Active Population (EAP) in Ecuador [18]. The affiliated population was predominantly male (57.8%) and geographically concentrated in the provinces of Pichincha (28.8%) and Guayas (25.4%). By economic activity, the services sector accounted for the largest proportion of affiliates (49.5%).

2.4 Variables and indicators

The primary unit of analysis was the certified non-fatal in-mission occupational road traffic injury. The following variables were examined: year of occurrence, sex, age group (≤24, 25–34, 35–44, 45–64, and ≥65 years), province of occurrence, and economic activity. Temporal characteristics included month, day of the week, and hour of occurrence.

Temporary disability (TD), defined as medically certified work absence of at least one day, was used as a proxy indicator of relative severity.

Three complementary indicators were calculated. First, frequency was described using absolute and relative distributions of all certified cases. Second, relative severity was defined as the proportion of cases resulting in temporary disability. Third, incidence was estimated as a population-burden indicator based on temporary-disability cases, using the following formula: IR = (number of in-mission road traffic injuries with temporary disability during 2023–2024 / mean affiliated population in June 2023 and June 2024) × 100,000. For sex-, age-, province-, and economic activity-specific incidence rates, the same approach was applied using the corresponding stratum-specific numerators and denominators. Because the available denominator reflects affiliated population counts rather than direct measures of road exposure or person-time at risk, these incidence rates should be interpreted as indicators of burden within the affiliated workforce rather than as direct estimates of individual crash risk.

2.5 Statistical analysis

Data cleaning and consistency checks were performed before analysis to ensure internal coherence and dataset integrity. A descriptive analysis was conducted for the overall 2023–2024 period. In accordance with the descriptive aim of the study, no causal modeling or multivariable inferential analysis was performed. All analyses were conducted using Microsoft Excel (version 16.78).

2.6 Bias and limitations

The study has several limitations inherent to the use of administrative records. First, the database did not include individual-level measures of road exposure, such as mileage, travel duration, or frequency of work-related travel. Accordingly, the incidence rates should be interpreted as indicators of population burden rather than as direct estimates of individual risk. Second, the use of routinely collected administrative data may involve variability in data quality, incomplete recording, or underreporting. Third, the findings reflect only workers affiliated with the IESS and therefore cannot be extrapolated to the entire Economically Active Population of Ecuador, particularly to workers in informal employment.

2.7 Ethical considerations

This study was based on a secondary anonymized administrative database. In accordance with the Organic Law on Personal Data Protection [19] and international ethical principles for research involving human data [20], no direct identification of individuals was possible. Administrative authorization for the use of the database and implementation of the study was formally granted by the GDOR-IESS. Given the use of anonymized secondary data and the absence of direct participant involvement, formal ethics committee review was not required under the applicable institutional and regulatory framework.

This study provides a descriptive characterization of work-related road traffic injuries occurring during the work shift (in-mission) among social security-affiliated workers in Ecuador and shows that these events constitute a relevant component of the occupational injury burden. Rather than representing isolated incidents, the observed pattern suggests that in-mission road traffic injuries should be understood within the intersection between occupational exposure to mobility demands and the broader road environment, in line with previous literature [4, 5].

In terms of magnitude, the findings are broadly consistent with international evidence identifying road traffic injuries as an important source of injury and disability among the working-age population [1-3]. Within the Ecuadorian Social Security system, the incidence reported in Table 1 supports the interpretation that these events represent a non-negligible occupational health problem. In this regard, the present study extends the national literature by addressing non-fatal in-mission events, whereas prior research in Ecuador has largely concentrated on fatal outcomes or selected economic sectors [9-12]. This additional evidence contributes to a more comprehensive epidemiological description of work-related road traffic injuries in the country.

The sex distribution, with a higher proportion of cases among men, is consistent with previous studies [6, 8]. A plausible explanation is the greater concentration of men in occupations involving work-related travel or higher occupational mobility. However, the participation of women should not be overlooked, particularly given that severe outcomes were also observed in this group. Although this pattern may reflect changes in labor market participation and mobility profiles, such an interpretation cannot be confirmed with the available data and therefore requires specific empirical support.

The concentration of cases in the 25–44-year age group is also epidemiologically plausible, as this age range corresponds to a large share of the economically active population [2, 3, 10]. This distribution may be associated with greater occupational exposure to travel demands during the most productive stages of working life. By contrast, the observation that younger workers appear to experience more severe outcomes warrants cautious interpretation. Although lower driving experience has been proposed as a possible explanatory factor in previous research [4], the present study does not directly assess this mechanism. Accordingly, this explanation should be considered hypothesis-generating rather than conclusive.

At the territorial level, the greater absolute number of cases in provinces such as Guayas and Pichincha is consistent with their higher concentration of economic activity and affiliated workers [18]. However, the presence of elevated incidence rates in smaller provinces suggests that the distribution of risk cannot be explained solely by workforce size. Contextual determinants, including road infrastructure, traffic enforcement, commuting patterns, or regional organization of work, may also contribute to these differences. Since these factors were not directly evaluated in the present analysis, their role should be interpreted cautiously and regarded as a priority for future research. Nevertheless, the findings indicate that geographic heterogeneity is a relevant feature of the burden of in-mission road traffic injuries in Ecuador.

The sectoral analysis further indicates that occupational road risk is not confined to transport-related activities. The high values observed in sectors such as finance, real estate, and services suggest that road exposure may be embedded in a wide range of jobs beyond professional driving. This interpretation is consistent with previous research showing that work organization factors, including time pressure, task demands, and workload, may shape occupational road risk [5]. From an occupational health perspective, this finding is important because it broadens the scope of prevention beyond traditionally recognized high-risk sectors. At the same time, the very high incidence rates observed in some activities should be interpreted cautiously because small affiliated populations may amplify stratum-specific rates.

The higher severity observed in sectors such as mining also deserves attention. One possible interpretation is that these sectors combine road traffic exposure with more complex occupational settings or multiple concurrent hazards [5, 9]. However, because the present analysis does not include detailed information on work processes, exposure profiles, or crash circumstances, this explanation remains tentative and requires further empirical or bibliographic support. Even so, the findings underscore that the burden of in-mission road traffic injuries should be evaluated not only in terms of frequency but also in terms of severity and functional consequences.

With respect to injury patterns, cervical injuries and lower-limb injuries accounted for the largest share of cases, with the neck being the single most frequently affected anatomical region. By contrast, abdomen, lumbosacral area, and pelvis represented only a small proportion of injuries. This pattern suggests that the burden of non-fatal in-mission road traffic injuries in this population is concentrated in body regions that may substantially affect short-term functional capacity and work performance. However, the anatomical distribution should be interpreted descriptively, as the database does not include detailed crash mechanics, vehicle type, or collision circumstances.

A key analytical contribution of the study lies in distinguishing in-mission from commuting road traffic accidents. This distinction is important because in-mission events are more directly linked to work activity, work organization, and employer-related preventive opportunities [4-6, 8]. Consequently, these events may be more amenable to intervention through occupational safety and health policies, organizational controls, and mobility management strategies. Framing in-mission road traffic injuries as an occupational risk rather than solely as a transport issue may therefore improve prevention planning and institutional response.

These findings should nevertheless be interpreted considering the study limitations. The use of administrative records may entail underreporting, classification errors, and inconsistencies in case registration [16]. In addition, the available database does not permit direct evaluation of potentially relevant explanatory variables such as road exposure, type of vehicle, occupational task, driving experience, organizational pressures, or road environment. As a result, several interpretations proposed in this discussion should be understood as plausible but not demonstrable with the present data. This limitation does not invalidate the descriptive value of the findings, but it does constrain causal interpretation and highlights the need for more analytically detailed studies.