Mortality Implications of Increased Active Mobility for a Proposed Regional Transportation Emission Cap-and-Invest Program.

The transportation sector is now the primary contributor to greenhouse gas emissions in the USA. The Transportation Climate Initiative (TCI), a partnership of 12 states and the District of Columbia currently under development, would implement a cap-and-invest program to reduce transportation sector emissions across the Northeast and Mid-Atlantic region, including substantial investment in cycling and pedestrian infrastructure. Using outputs from an investment scenario model and the World Health Organization Health Economic Assessment Tool methodology, we estimate the mortality implications of increased active mobility and their monetized value for three different investment allocation scenarios considered by TCI policymakers. We conduct these analyses for all 378 counties in the TCI region. We find that even for the scenario with the smallest investment in active mobility, when it is fully implemented, TCI would result in hundreds of fewer deaths per year across the region, with monetized benefits in the billions of dollars annually. Under all scenarios considered, the monetized benefits from deaths avoided substantially exceed the direct infrastructure costs of investment. We conclude that investing proceeds in active mobility infrastructure is a cost-effective way of reducing mortality, especially in urban areas, providing a strong motivation for investment in modernization of the transportation system and further evidence of the health co-benefits of climate action.

Disparities in Activity and Traffic Fatalities by Race/Ethnicity.

INTRODUCTION: Traffic fatalities remain a major public health challenge despite progress made during recent decades. This study develops exposure-based estimates of fatalities per mile traveled for pedestrians, cyclists, and light-duty vehicle occupants and describes disparities by race/ethnicity, including a subanalysis of fatality rates during darkness and in urban areas. METHODS: Estimates of person-miles traveled by mode and race/ethnicity group were derived from the 2017 National Household Travel Survey using replicate weights. Three-year average (2016‒2018) traffic fatalities were measured by mode and race/ethnicity group with the U.S. Fatality Analysis Reporting System. Fatality rates per mile traveled and CIs were calculated for each subgroup as well as separately for trips occurring during darkness and in urban areas. Analysis was conducted in 2021‒2022. RESULTS: Exposure to traffic fatality differs by race/ethnicity group and by mode, indicating that adjustment for differential exposure is needed when estimating disparities. The authors find that fatality rates per 100 million miles traveled are systematically higher for Black and Hispanic Americans for all modes and notably higher for vulnerable modes (e.g., Black Americans died at more than 4 times the rate for White Americans while cycling, 33.71 [95% CI: 21.84, 73.83] compared with 7.53 [95% CI: 6.64, 8.69], and more than 2 times the rate while walking, 40.92 [95% CI: 36.58, 46.44] compared with 18.77 [95% CI: 17.30, 20.51]). Previous estimates that do not adjust for differential exposure may underestimate disparities by race/ethnicity. Observed disparities remained when considering only urban areas and appear to be exacerbated during darkness. CONCLUSIONS: Traffic fatalities are a substantial and preventable public health challenge in America. Black and Hispanic Americans have higher traffic fatality rates per mile traveled than White Americans across the transportation system, requiring urgent attention.

Structural Racism and COVID-19 in the USA: a County-Level Empirical Analysis.

Substantial health disparities exist across race/ethnicity in the USA, with Black Americans often most affected. The current COVID-19 pandemic is no different. While there have been ample studies describing racial disparities in COVID-19 outcomes, relatively few have established an empirical link between these disparities and structural racism. Such empirical analyses are critically important to help defuse "victim-blaming" narratives about why minority communities have been badly hit by COVID-19. In this paper, we explore the empirical link between structural racism and disparities in county-level COVID-19 outcomes by county racial composition. Using negative binomial regression models, we examine how five measures of county-level residential segregation and racial disparities in socioeconomic outcomes as well as incarceration rates are associated with county-level COVID-19 outcomes. We find significant associations between higher levels of measured structural racism and higher rates of COVID-19 cases and deaths, even after adjusting for county-level population sociodemographic characteristics, measures of population health, access to healthcare, population density, and duration of the COVID-19 outbreak. One percentage point more Black residents predicted a 1.1% increase in county case rate. This association decreased to 0.4% when structural racism indicators were included in our model. Similarly, one percentage point more Black residents predicted a 1.8% increase in county death rates, which became non-significant after adjustment for structural racism. Our findings lend empirical support to the hypothesis that structural racism is an important driver of racial disparities in COVID-19 outcomes, and reinforce existing calls for action to address structural racism as a fundamental cause of health disparities.