Results: According to the simulation results obtained from two base case scenarios for corn ethanol and soy biodiesel, we find that producing 15 BGs of corn ethanol and 2 BGs gallons of soy biodiesel together could potentially increase area of cropland in M&I by 59.6 thousand hectares. That is less than 0.5% of the cropland expansion in M&I for the time period of 2000-2016, when biofuel production increased in the US. The original GTAP-BIO model parameters including the regional substitution rates among vegetable oils were used for the base case scenarios. The estimated induced land use change (ILUC) emissions values for corn ethanol and soy biodiesel are about 12.3 g CO2e MJ-1, 17.5 g CO2e MJ-1 for the base case scenarios. The share of M&I in the estimated ILUC emissions value for corn ethanol is 10.9%. The corresponding figure for soy biodiesel is much higher, 78%. The estimated ILUC emissions value for soy biodiesel is sensitive with respect to the changes in the regional rates of substitution elasticity among vegetable oils. That is not the case for corn ethanol. When we replaced the original substitution elasticities of the base case, which are very large (i.e., 5 or 10) for many regions, with a small and uniform rate of substitution (i.e., 0.5) across the world, the ILUC emissions value for soy biodiesel drops from 17.5 g CO2e MJ-1 to 10.16 g CO2e MJ-1. When we applied larger substitution elasticities among vegetable oils, the estimated ILUC emissions value for soy biodiesel converged towards the base case results. This suggests that, other factors being equal, the base case substitution elasticities provide the largest possible ILUC emissions value for soy biodiesel. Finally, our analyses clearly indicate that those analyses that limit their modeling framework to only palm and soy oil and ignore other types of vegetable oils and fats provide misleading information and exaggerate about the land use implications of the US biofuels for M&I.
Conclusion: (1) Production of biofuels in the US generates some land use effects in M&I due to market-mediated responses, in particular through the links between markets for vegetable oils. These effects are minor compared to the magnitude of land use change in M&I. However, because of the high carbon intensity of the peatland the emissions fraction of M&I is larger, in particular for soy biodiesel. (2) The GTAP-BIO model implemented a set of regional substitution elasticities among vegetable oils that, other factors being equal, provides the largest possible ILUC emissions value for soy biodiesel. (3) With a larger substitution elasticity among all types of vegetable oils and animal fats in the US, less land use changes occur in M&I. That is due to the fact that a larger substitution elasticity among vegetable oils in the US, diverts a larger portion of the additional demand for soy oil to non-palm vegetable oils and animal fats that are produced either in the US or regions other than M&I. (4) Those analyses that limit their modeling framework to only palm and soy oils and ignore other types of vegetable oils and fats provide misleading information and exaggerate about the land use implications of the US biofuels for M&I.
METHODS: This was a retrospective cohort study of 859 community-dwelling patients aged ≥70 years treated at 15 primary care practices. Patients were asked if they had experienced any of a list of 74 symptoms classified by physiologic system in the previous 6 months and if (1) they believed the symptom to be related to their medication, (2) the symptom had bothered them, (3) they had discussed it with their family physician, and (4) they required hospital care due to the symptom. Self-reported symptoms were independently reviewed by 2 clinicians who determined the likelihood that the symptom was an ADE. Family physician medical records were also reviewed for any report of an ADE.
RESULTS: The ADE instrument had an accuracy of 75% (95% CI, 77%-79%), a sensitivity of 29% (95% CI, 27%-31%), and a specificity of 93% (95% CI, 92%-94%). Older people who reported a symptom had an increased likelihood of an ADE (positive likelihood ratio [LR+]: 4.22; 95% CI, 3.78-4.72). Antithrombotic agents were the drugs most commonly associated with ADEs. Patients were most bothered by muscle pain or weakness (75%), dizziness or lightheadedness (61%), cough (53%), and unsteadiness while standing (52%). On average, patients reported 39% of ADEs to their physician. Twenty-six (3%) patients attended a hospital outpatient clinic, and 32 (4%) attended an emergency department due to ADEs.
CONCLUSION: Older community-dwelling patients were often not correct in recognizing ADEs. The ADE instrument demonstrated good predictive value and could be used to differentiate between symptoms of ADEs and chronic disease in the community setting.