Road crashes remain a preventable cause of morbidity and mortality. The rush-hour period represents the time with the highest human and vehicular road densities. This dissertation aims to assess, during the rush and non-rush hour periods, the environmental factors associated with fatal crash injuries, the association of substance use and non-fatal crash injuries, and the association of crash response time and deaths at crash scenes. To address the first aim, data from the Fatality Analysis Reporting System was used. We limited the data to crashes during the rush hour period. The outcome variable was the fatal crash counts per county. The predictor variables were road design (intersection, driveway, ramp, work-zone), road type (interstate, highways, roads/streets), and inclement weather factors (rain, fog, snow). A nested spatial negative binomial regression model was used to estimate the incidence rate ratio of fatal crash injury during the rush hour period. To address the second aim, Crash data were extracted from the 2019 National Emergency Medical Services Information System data. The outcome variable was non-fatal crash injury, assessed on an ordinal scale – critical, emergent, and low acuity. The predictor variable was the presence of substance use (alcohol or illicit drugs). Age, gender, region of the body injured, and the revised trauma score was used as potential confounders. Partially proportional ordinal logistic regression was used to assess the unadjusted and adjusted odds of critical and emergent outcomes compared to low acuity patients. To address the third aim, data from the 2019 National Emergency Medical Services (EMS) Information System was used. The outcome variable was death-at-the-scene. The predictor variables were the crash response times – crash notification (EMS notification to departure from the base station) and EMS travel time (base station to crash scene). Age, gender, substance use, region of the body injured, the revised trauma score, and rurality/urbanicity of each injury location were used as potential confounders. Logistic regression was used to assess the unadjusted and adjusted odds of death-at-the-scene. During the rush-hour period, the median fatality rate per county was 7.30 per 100,000 population. Highways had the highest fatality risk, after adjusting for the interaction effect of intersection, driveway, ramp, and work-zone. Also, after adjusting for confounders, Substance use was associated with 2.09 (95% CI: 2.03 - 2.14) and 2.26 (95% CI: 2.14 – 2.38) odds of emergent and critical injury outcomes as compared to low acuity at all times of the day and during the rush hour period, respectively. After adjusting for confounders, a minute increase in the EMS travel time was associated with 0.4% (Adjusted OR: 1.004; 95% CI: 1.003 – 1.006) and 0.7% (Adjusted OR: 1.007; 95% CI: 1.005 – 1.009) increased odds of death-at-the-scene during all times of the day and the rush-hour period, respectively. This dissertation reports that certain environmental factors, substance use, and crash response times are significantly associated with fatal and non-fatal crash injuries. Also, the rate ratios and odds of fatal and non-fatal crash injuries are heightened during the rush hour period.