A total of 6,580 male and 4,382 female surviving drivers were entered in the final analyses, which were weighted to represent a national sample of 2, 965, 332 male and 2, 392, 936 female drivers, respectively. The characteristics of the sample stratified by sex are presented in . The table presents the means for continuous variables and proportions for categorical variables and their 95% CIs for driver, vehicle, collision, and environmental factors. Male drivers were significantly younger, taller, heavier, and had larger BMIs than female drivers, respectively. More MVCs occurred among female drivers when driving passenger cars than among male drivers. Female drivers were also more likely to drive newer and lighter vehicles than were male drivers. Male drivers had greater percentages vehicle rollover and lower percentages of seat belt use than did female drivers. Male drivers were more likely to be involved in MVCs involving single vehicle. Male drivers were more likely to be involved in MVCs at night. No sex differences were found for age, race, alcohol use, drug use, airbag deployment, ejection, or weather conditions.
Characteristics of the sample of surviving drivers involved in motor vehicle crashes
There was no significant difference in the mean ISS between injured male and female drivers. Male drivers endured a lower rate of overall injury (ISS>0, 38.1% vs. 52.2%) but higher rate of severe injury (ISS>24, 0.7% vs. 0.2%) compared with female drivers.
The results of the binary logistic models for testing the association between risk of non-fatal injury and BMI (or BMI and BMI2 for curvilinear relations) in male drivers, female drivers, and pooled drivers in the All Subjects model (left) and the ΔV Model (right) are summarized in . Covariates were adjusted in all models, including age, race, alcohol involvement, drug involvement, type of vehicle, vehicle age, curb weight, seat belt use, air bag deployed, ejection, rollover, involved vehicle number, road speed limit, light condition, weather condition, and ΔV (for ΔV Model). The adjusted odds ratios (ORs) derived from logistic regression coefficients for 28 BMI points from 18 to 45 kg/m2 are shown in and . The mean BMI of 26.0 kg/m2 was used as the reference in male drivers (upper panel) and female drivers (lower panel) in both the All Subjects Model () and the ΔV Model (). In the All Subjects Model, a U-shaped association was identified between risk of moderate-plus injury (ISS>8) and obesity in male drivers (logistic coefficient of BMI=−0.4113, p<0.01; logistic coefficient of BMI2=0.0075, p<0.01), which means that lean and obese male drivers (both ends of the BMI continuum) endured a higher risk of moderate-plus injury (ISS>8) than did normal male drivers. However for female drivers, an inverted U-shaped association was found between risk of moderate-plus injury (ISS>8) and BMI (logistic coefficient of BMI=0.4227, p<0.01; logistic coefficient of BMI2=−0.0073, p<0.01). Obese male drivers showed much higher risks of serious-plus injury (ISS>15) and severe-plus injury (ISS>24) than normal male drivers. In the ΔV Model, all the associations derived from the regression models were postulated within the same collision conditions during the MVCs. The associations between obesity and non-fatal injuries were more evident with these conditions. Obese male drivers experienced progressively increasing risks of moderate-plus injury, serious-plus injury, and severe-plus injury compared with nonobese male drivers (logistic coefficient of BMI=0.0766, 0.1470, and 0.1792, respectively; all p<0.05). Sex differences in the patterns of associations with obesity were observed in the risk of moderate-plus injury (ISS>8), serious-plus injury (ISS>15) and severe-plus injury (ISS>24) in both the All Subjects Model and the ΔV Model. With similar directions and trends in both models, the figures highlight that the risk of non-fatal injury increased more dramatically with BMI for male drivers than for female drivers; furthermore, these sex differences increased with the severity of injury, especially after control for ΔV.
Results of the binary logistic regression models testing the association between risk of non-fatal injury and BMI
Figure 1 Predicted adjusted odds ratios (ORs) for the risk of non-fatal injury by BMI in the All Subjects Model. A mean BMI of 26.0 kg/m2 was considered as the reference. Adjusted odds ratios for each BMI point were calculated from coefficients from 18 to 45 by (more ...)
Figure 2 Predicted adjusted odds ratios (ORs) for the risk of non-fatal injury by BMI in the ΔV Model. A mean BMI of 26.0 kg/m2 was considered as the reference. Adjusted odds ratios for each BMI point were calculated from coefficients from 18 to 45 by (more ...)