Our results reveal a strong association between PCDR and both increased age and male gender, in accordance with almost all previous studies (Chang 2008; Mabunda et al. 2008). The association between death and age is strongly related with increased fatality in older pedestrians, in agreement with many previous studies (Chang 2008; Henary et al. 2006; Kim et al. 2008; Mohamed et al. 2013; Tefft 2013); this association is usually explained by the increased frailty associated with ageing (Kim et al. 2008; Tarko and Azam 2011). However, the role of the other two components (i.e., exposure and risk of crash) remains uncertain, partially because it is difficult to determine the amount of exposure in pedestrians accurately (Clifton and Livi 2005; Keall 1995). Unlike previous studies (Keall 1995; Milligan et al. 2013; Mindell et al. 2012; Zhu et al. 2013), we used a quasi-induced exposure method based on comparisons of the age and gender distribution of “innocent” pedestrians involved in clean collisions with age and gender in the whole population. In doing so, we took into consideration only the exposure windows in which pedestrians can be considered at fault or not at fault for a collision (i.e., while they are crossing or walking along a roadway), and therefore at risk of being struck by a vehicle. With this method, the amount of exposure increased with age from 45 years old onward; therefore, it also contributed to the direct association between ageing and higher PCDR. This result is not surprising: older pedestrians are exposed to the risk of collision with a vehicle for longer periods because they need more time to walk the same length-at-risk (typically, crossing a road) (Avineri et al. 2012; Hoxie and Rubenstein 1994; Keall 1995; Oxley et al. 1997; Romero-Ortuno et al. 2010). These results thus emphasize the need to develop interventions intended to compensate for this handicap in older pedestrians, by (for example) lengthening traffic light times for crossing (Hoxie and Rubenstein 1994; Romero-Ortuno et al. 2010) or building median strips to facilitate crossing two-lane roads (Oxley et al. 1997).
Another interesting finding from our study is the inverse association between age and the risk of involvement in a crash adjusted by exposure. As widely reported for pedestrians and other types of road users (Cestac et al. 2011; Ivers et al. 2009; Sullman et al. 2011), this risk is higher for the youngest pedestrians. Pollack et al. reported that younger pedestrians, such as students, engage in risky behaviors in terms of distracted walking (e.g., walking while talking or texting on a cell phone, or listening to music on an iPod) (Pollack et al. 2014). Furthermore, in our study the lowest risk is seen in the oldest pedestrians. This is in agreement with previous findings that older people take fewer risks (Bernhoft and Carstensen 2008), are less likely to attempt to cross in risky situations (Holland and Hill 2007), and adopt safer behaviors when crossing a street (Keall 1995; Oxley et al. 1997).
Regarding the role of gender, our results are also in agreement with previous studies that found higher PCDR in males than females (Chang 2008; Zhu et al. 2013), although the strength of this association changed with age. Decomposition analysis revealed, in accordance with a study by Zhu et al. (2013), that fatality is again the most important determinant of the higher PCDR in males. This finding has also been observed in previous studies (Chang 2008; Clifton et al. 2005; Zhu et al. 2013), although the reasons for this association are not well understood. One hypothesis is that compared to females, male pedestrians are involved in collisions of higher intrinsic severity. For example, it has been reported that collisions at night (in which males may be involved more frequently because females tenfd to walk less at night than males (Clifton and Livi 2005) are more severe than those that occur during daylight (Kim et al. 2008).
In accordance with previous studies (Keall 1995; Zhu et al. 2013), we also found that the risk of involvement in a crash adjusted by exposure is higher in male pedestrians than in females, especially in younger age groups. It has been shown that pedestrian women are more sensitive to traffic safety than men, and appear to engage in fewer risk-taking behaviors (Clifton et al. 2005; Clifton and Livi 2005; Holland and Hill 2007; Sullman et al. 2011). Ulfarsson et al. observed that male pedestrians were more likely to be solely at fault than females in pedestrian–motor vehicle crashes (Ulfarsson et al. 2010). Furthermore, Faria et al. (2010) found that males tended to follow others pedestrians crossing a road more frequently than females. The higher fatality and risk of involvement in a crash in males compared to females is partially counterbalanced by their lower amount of exposure, observed for males of all ages except the extreme age groups. This may be related with both the amount of walking, which is greater in females according to some studies (Keall 1995), and with the speed of walking, which is faster in males than in females (Avineri et al. 2012; Miguel 2013).
Our study has several limitations. First, we used a police-based registry. Hypothetically, and as noted in other countries (Lopez et al. 2000; Sciortino et al. 2005), the Spanish registry tends to underestimate less severe crashes and collisions in urban areas. This is especially relevant in collisions involving pedestrians, because they occur mainly in urban areas. We must therefore assume that we used a biased sample of crashes involving pedestrians: the pattern depicted by our decomposition model may be more applicable to severe crashes. However, severe crashes are those of greatest concern from a public health perspective, because they should constitute the primary focus of preventive interventions. The overrepresentation of more severe crashes (i.e., those that resulted in deaths or severe injuries) in police databases may also lead to frailty bias (Langford et al. 2006), which would lead to overestimation of the ERR for the oldest pedestrians, and underestimation of their FRR.
Furthermore, as shown in the flowchart in Fig. 1, we were obliged to exclude a number of pedestrians in the original database because the traffic police had not recorded whether they and/or the driver involved in the crash had committed an infraction. Most of these missing cases occurred in specific provinces (and from specific years onward) where the traffic police were not required to record this information. We can offer no hypotheses regarding the direction or magnitude of this possible selection bias. Moreover, the Spanish register includes only deaths that occur within the first 24 h after a crash. The subsequent underestimation of fatality rates may differ for different age groups if we assume that increasing age is related with a worse prognosis for crash-related injuries.
Several concerns have been raised about quasi-induced exposure methods when applied to other road users (Jiang and Lyles 2010). For example, it may be difficult to identify the party responsible for the crash from information in the police-based registry regarding whether an infraction was committed, and whether the infractor was the pedestrian or the driver of the vehicle. It is important to emphasize that the way we assigned responsibility was not deterministic, but probabilistic: in a collision between a pedestrian who had not committed an infraction and a vehicle whose driver had just committed an infraction, the driver was much more likely to be at fault for the collision than the pedestrian. Doubts may also arise regarding the validity of our assumption that the age and gender distribution in our sample of non-responsible pedestrians is representative of the whole population of exposed pedestrians. In this connection it is important to emphasize that our estimate of exposure did not include the whole time or the entire distance walked on sidewalks or pedestrian streets. Finally, the decomposition method assumes that each conditional probability is independent of and not confounded with other probabilities, whereas in fact the effects are likely to overlap (Goldstein et al. 2011) and depend upon the classified groups being relatively homogenous.