Sex and Racial Differences in Autopsy-Defined Causes of Presumed Sudden Cardiac Death

Background - Sudden cardiac death (SCD) studies report higher incidence in men and Blacks but presume cardiac cause. We sought to identify sex and race differences in rates and causes of presumed SCDs in a prospective postmortem study in San Francisco County. Methods - All incident presumed SCDs meeting World Health Organization definition ages 18-90 were autopsied via active surveillance of consecutive out-of-hospital deaths in the PO stmortem S ystematic Inves T igation of S udden C ardiac D eath (POST SCD) Study (2/1/2011 - 3/1/2014). Autopsy-defined sudden arrhythmic deaths (SADs) had no extra-cardiac cause or acute heart failure. Results - Among 541 presumed SCDs, 525 (97%) were autopsied; 362 (69%) were male, 110 Asian (21%), 81 Black (15%), 40 Hispanic (8%), 279 White (53%), and 15 Other Race (3%). Adjusted for age and race, women had more non-cardiac causes of presumed SCD, including pulmonary emboli (8% vs. 2%) and neurologic causes (10% vs. 3%, both p<0.01). Of autopsy-defined SAD, men had 3-fold higher rates while women had more primary electrical disease (4% vs. 2%, p=0.02) and non-ischemic causes (53% vs. 39%, p<0.01). Age-adjusted incidence rate ratios were higher for Black women (2.55, p<0.01), and lower for Asian and Hispanic men (0.51 for both, p<0.05) than their White counterparts. Myocardial infarction without obstructive coronary arteries was more common among SADs in Asians than Whites (7% vs. 1%; adjusted p<0.05). Sudden neurologic deaths were more common in Asians, endocrine causes more common in Blacks, and gastrointestinal causes more common in Hispanics than Whites (adjusted p all <0.05). Conclusions - In this countywide postmortem study of presumed SCDs, women had more non-ischemic and non-cardiac causes. Black women had higher rates of autopsy-defined SAD than White women while Asian and Hispanic men had lower rates than White men. These findings have implications for risk stratification and prevention of sudden mortality in women and minority populations.

Steep increases in fentanyl-related mortality west of the Mississippi River: synthesizing recent evidence from county and state surveillance

ABSTRACTBackground and AimsOverdose deaths from synthetic opioids (e.g., fentanyl), increased 10-fold in the United States from 2013-2018, despite 88% of deaths occurring east of the Mississippi River. Public health professionals have long feared that further spread of fentanyl could greatly exacerbate the opioid epidemic. We aimed to measure and characterize recent fentanyl deaths in jurisdictions west of the Mississippi River.DesignSystematic search of states and counties in the Western U.S. for publicly available data on fentanyl-related deaths since the most recently published Centers for Disease Control and Prevention (CDC) statistics, which cover through December 2018. Longitudinal study using 2019 and 2020 mortality records to identify changes in fentanyl-involved mortality since most recent CDC statistics.SettingsU.S. states west of the Mississippi River.MeasurementsAnnual rate of fentanyl-involved deaths per 100,000 population. Proportion of fatal heroin-, stimulant, and prescription pill overdoses also involving fentanyl.FindingsWe identified nine jurisdictions with publicly available fentanyl death data through December 2019 or later - State of Arizona; Denver County, CO; Harris County, TX; Humboldt County, CA; King County, WA; Los Angeles County, CA; San Francisco County, CA; Siskiyou County, CA; Dallas-Fort Worth, TX metro area (Denton, Johnson, Parker, Tarrant counties. Fentanyl deaths increased in each jurisdiction. Their collective contribution to national synthetic narcotics mortality tripled from 2017 to 2019. First quarter 2020 data (available from all but San Francisco County) showed a 33% growth in fentanyl-mortality over 2019. Fentanyl-involvement in heroin, stimulant, and prescription pill deaths has grown substantially over time.ConclusionsFentanyl has spread westward, which could dramatically worsen the nation’s already severe opioid epidemic. Increasing standard-dose of naloxone, expanding Medicaid, improving coverage of addiction treatment, and public health educational campaigns should be prioritized.

Profiling Transport Network Company Activity using Big Data

Transportation network companies (TNCs) provide vehicle-for-hire services. They are distinguished from taxis primarily by the presumption that vehicles are privately owned by drivers. Unlike taxis, which must hold one of approximately 1,800 medallions licensed by the San Francisco Municipal Transportation Agency (SFMTA) to operate in San Francisco, there is no regulatory limit on the supply of TNCs. TNCs have an increasingly visible presence in San Francisco. However, there has been little or no objective data available on TNCs to allow planners to understand the number of trips they provide, the amount of vehicle miles traveled they generate, or their effects on congestion, transit ridership, transit operations, or safety. Without this type of data it is difficult to make informed planning and policy decisions. Discussions with Uber, Lyft, and the California Public Utilities Commission, which collects trip-level data from TNCs in California, requesting information on TNC trips have not resulted in any data being shared. Under increasing pressure from policymakers for objective data to inform policy decisions, the San Francisco County Transportation Authority (SFCTA) partnered with researchers from Northeastern University who developed a methodology for collecting data through Uber’s and Lyft’s application programming interfaces (APIs) with high spatial and temporal resolution. This paper provides a brief literature review on transport network company (TNC) data, and goes one to describe the methodology used to collect data, summarizes the process for converting the raw data into estimated TNC trips, and presents an analysis of the results of the TNC trip estimates. This study determined that TNCs serve a substantial number of trips in San Francisco, over 170,000 on a typical weekday, that these trips follow traditional time of day distributions, and that they tend to take place in the busiest parts of the City.

Getting People Around After the Trains Stop Running

Late-night transit service provides an important connection to jobs, entertainment venues, and other destinations in San Francisco, California, and other major cities. In 2016, the San Francisco County Transportation Authority led a comprehensive reexamination of the region’s late-night bus network, which provided service between about midnight and 5:00 a.m., while the region’s rail services were closed for maintenance. Previous literature established the general characteristics of late-night transit users and trip generators but did not develop and validate the use of a specific tool to plan service. Other researchers also developed transit propensity indexes (TPIs) with the use of demographic data for transit service in general but not specifically for the late-night period. A new approach was used to assess transit demand for late-night work trips by using Census Transportation Planning Package data to identify late-night work trips and combining those trip volumes with additional demographic factors associated with reliance on public transit to develop a late-night TPI. The hypothesis was that high TPI scores were an indicator of areas where late-night transit would attract strong ridership. The research team compared the index results with ridership on existing routes by using a stop-level regression analysis to validate that the TPI is predictive of ridership at a statistically significant level. It was concluded that the TPI together with productivity analysis of existing routes supported identification of potential late-night transit network changes to improve coverage in areas where riders would most need and use the service.

REGRESSION MODEL PREDICTING THE APPRAISED UNIT VALUE OF LAND IN SAN FRANCISCO COUNTY BASED ON LEED-NC PUBLIC TRANSPORTATION ACCESS CRITERIA

As the need for environmental certification systems grows, Leadership in Energy and Environmental Design for New Construction (LEED-NC) is being widely adopted in the US to evaluate the environmental performance of buildings. However, no research has been conducted to investigate its economic impact on appraised land value. The objectives of this study are to quantify the impact of the LEED-NC Credit Alternative Transportation: Public Transportation Access (PTA) in the sustainable sites category on appraised land value and to develop a regression model that predicts the appraised unit value of parcels. San Francisco County was chosen because of its well-organized transportation systems. First, a LEED-NC map was created to identify PTA-qualified parcels. Second, sample parcels were randomly selected. Last, Pearson's correlation analysis, one-way ANOVA, and multiple linear regression analysis were sequentially performed. The results of this study indicated that the LEED PTA criteria are significant factors associated with an increase in the appraised unit value of parcels within San Francisco County. The findings of this study can encourage real-estate developers to site their projects according to the LEED-NC PTA criteria.