ITHIM Implementation. To communicate the public health benefits of active transportation projects to the residents in the region, GNRC worked with the Centers for Disease Control and Prevention (CDC) to estimate the monetary value of the benefits by using the Integrated Transportation and Health Impact Modeling Tool (ITHIM) (Xxxxxx and Xxxxxxxxx, 2017). Technical details of ITHIM and the calibration data used for the Nashville implementation had been described in the literature review chapter. Figure 10 provides an overview of the ITHIM modeling process for the Nashville implementation (Xxxxxx, 2015). Source: Xxxxxx (2015) Figure 10 The ITHIM modeling process. Health outcomes resulting from investments in pedestrian and bicycle facilities are estimated by ITHIM with the relative risk method, which predicts the risk of developing respiratory and chronic diseases based on the amount of exposure to air pollution and physical activity involvement (Xxxxxx and Xxxxxxxxx, 2017). Active transportation increases physical activity and reduces air pollution. However, increasing pedestrian and bicyclist activities can also increase risk of traffic injuries and fatalities. Table 21 shows that lists of diseases whose risks of development are modeled in ITHIM with exposures to physical activity and air pollution (Xxxxxx, 2015). Table 21Exposures and Diseases Modeled by ITHIM Exposure to Physical Activity Exposure to Air Pollution Ischemic Heart Disease Respiratory Infections Depression Cardiovascular Disease Dementia Hypertensive Heart Disease Diabetes Inflammatory Heart Disease Colon Cancer Lung Cancer Breast Cancer Respiratory Disease (kids) All‐Cause Mortality Stroke
ITHIM Implementation. 3.3.2.1 Calibration Data Baseline disease burden data were obtained from the 2010 U.S. Global Burden of Disease, data (IHME, 2015), using DALYs as the measure of disease burden. Baseline all-cause mortality rates for the Sacramento region were based on the 2008-2010 California Department of Public Health (CDPH) Vital Records Data and Statistics (CDPH, 2020). Baseline leisure time physical activity data are from the California Health Interview Survey (UCLA, 2008). Baseline and scenario-specific data on travel distance by automobiles, trucks, and active transportation were derived from Sacramento Activity-Based Travel Simulation Model (SACSIM15) (SACOG, 2015), SACOG’s regional travel demand model. Baseline traffic fatalities and injuries for the Sacramento region were obtained from the Statewide Integrated Traffic Records System and the Transportation Injury Mapping System (XXXX) (SafeTREC, 2020). To disaggregate regional data to ZIP code areas, demographic (i.e., population, age, and gender) data at the ZIP code level were obtained from the 2010 U.S. Census for all zip code tabulation areas (ZCTA) within the SACOG region. Baseline mortality rates for each ZCTA are estimated by multiplying the ZCTA’s number of people in each age-gender category with corresponding Sacramento region-wide mortality rate for the same category. Leisure time physical activity data were estimated for each ZCTA with the same method. Data on scenario-specific active transportation activities were available at the traffic analysis zone (TAZ) level from SACSIM15 outputs. While most TAZ boundaries were identical to ZCTA, some TAZs were larger than ZCTAs. For TAZs that cover more than one ZCTA, the data of the TAZ were proportionally distributed to the ZCTAs based on the respective ZCTA areas covered by the TAZ. Baseline injury data were first stratified by striking and victim modes, severities, and road types (Rowangould, Karner, Xx, Igbinedion, and London, 2017). Region- wide fatality and injury rates for each stratum were factored into each ZCTA based on the ratio of miles traveled for each mode between each ZCTA and the region.
ITHIM Implementation. 3.2.2.1 Calibration Data Travel behavior data such as average daily distances traveled by walking and bicycling were derived from the 2012 California Household Travel Survey (CHTS) (NuStats, 2013). Travel demand models of the MPOs (i.e., San Francisco Bay Area, Southern California, and San Xxxxxxx Valley) as well as the California Statewide Travel Demand Model (i.e., for Sacramento Area and San Diego County) (West, 2016) provided estimates of daily vehicle miles traveled (VMT) for cars and trucks. Burden of disease of the study area was measured by deaths and disability adjusted life years (DALYs), which represent the sum of years of life lost to premature death and years of living with disability. Data on deaths and DALYs were obtained from the 2010 U.S. Global Burden of Disease, GBD (IHME, 2019). The disease burden data for each of the California MPOs were derived by adjusting the U.S. data with the ratio of mortality rates between counties in the MPO and the U.S. Data on weekly non-travel physical activity for leisure and occupational activities were obtained from the California Health Interview Survey (UCLA Center for Health Policy Research, 2012). Data on traffic fatalities and injuries were obtained from a statewide database of traffic collisions in California (SafeTREC, 2011). GHGE from cars and light trucks were estimated for each MPO region from modeled emission factors in 2010 (CARB, 2020b).
