## 3 Results
### Objective II
  
* Statistically significant individual predictors at \(\alpha=0.05\) (considering \(p\)-value \(<\) a). ** Statistically significantspecific injuries to turn into disability. Among occupations, poultry/egg producers (1.62), gas/oil dealers (1.55), and grain elevator operations (1.38) have the highest likeliness of incidents leading to disability compared to occupations in stores (meat, fish, and poultry). Looking at the odds ratios for occupations, those incidents in sales are all less likely to end as disability and have a higher probability of having a medical state only. Industry-wise, food distributors, livestock feed mills, and grain milling plants are between 1.02 and 1.39 times more likely to cause a disability outcome. Considering the Exp (95% CI), if the odds ratio of a specific variable is greater than 1 with the odds ratio of the lower bound confidence interval not being below 1, the variable in question is likely to pose a significant risk in incident occurrence. Among all incident causes, the highest risks of occupational incidents were found for the fall, slip, or trip injury category, with an odds ratio of 1.86 and a 95% CI of (1.70, 2.50), followed by \"caught in/under/between\" (odds ratio of 1.57 and 95% CI: (1.28, 1.92)) and the \"strain or injury by\" group (odds ratio of 1.49 and 95% CI: (1.35, 1.65)), respectively. These three categories could be identified as the most important risk indicators of incident cause. The highest risk occupations were gas/oil dealers and grain elevator operations (with odds ratio of 1.51 and 0.38 and 95% lower confidence interval of 1.28, and 1.20, respectively). Considering the cause of incident group, Figure 1 shows that when an incident occurred due to a vehicle, strain or injury by, and slip, trip, or fall injury categories, the probability of the disability post-incident state increased. The lowest disability probability belonged to those incidents caused by a cut, puncture, or scrape. All other causes of incident showed an average probability of disability between 0.10 and 0.30. As shown in Figure 2, among all levels of the injured body part group, the highest probability of disability post-incident state belonged to lower and upper extremities, followed by multiple body parts, trunk, neck, and the whole body group. Injuries to the head had the lowest probability of turning into disability (less than 10% on average). Figure 3 revealed the average probability of disability with respect to the nature of incidents. The multiple injury category had the highest probability of turning into disability (\(>\)40%), followed by occupational disease and specific injuries. However, for some specific cases, the specific injuries had a disability probability of over 0.50 (50% chance). Figure 1: Boxplot of disability post-incident state for each cause group. (* shows the outlier data points). Figures 4 and 5 show the boxplots for the probability of a disability post-incident state with respect to industry and occupation. All industries showed similar probabilities for disability (less than 50%), with some injuries having over a 50% chance of turning into a disability for occupations in grain elevators, fuel refining, and feed mill for livestock and pet foods. The probability of disability varied among occupations from 10% to 20%. Looking at the effect of age and years of experience at the accident date on the post-incident state of the injured, the former showed an upward trend, while the latter showed a weak linear trend. The analysis showed that higher age of workers affects the probability of disability (corresponding with the positive coefficient \(\beta=0.02\) from the model). The trend in this study agreed with previous literature on the effect of older ages on higher frequency and severity level of incidents, specifically when the occupation includes manufacturing operations, due to the effect of age on the physical activity and attention of the workers [1; 36; 37; 38; 39].