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Clinio Lofton
The Framingham Heart Study newsletter is produced once each year in the late winter or early spring. It is sent to the over 7,000 participants in the Heart Study all over the world and includes articles pertaining to current research, upcoming examination cycles, newsworthy past and upcoming events, and contact information of importance to our participants.
We encourage our participants to review the current FHS Examination informed consent form prior to their attendance at their research study appointment. We also have made past informed consent forms available.
The Framingham Heart Study welcomes the interest and proposals of outside investigators. Collaboration is encouraged as it helps to maximize the scientific value of the wealth of epidemiologic data made possible by the participation of more than 15,000 individuals who enrolled in the Framingham Heart Study over the past decades.
FHS has joined the Collaborative Cohort of Cohorts for COVID-19 Research (C4R Study), a nationwide study of more than 50,000 individuals to determine factors that predict disease severity and long-term health impacts of COVID-19.
The Framingham Heart Study encourages the interest and proposals of investigators in order to maximize the scientific value of epidemiologic data from the more than 15,000 individuals who have enrolled in FHS over the past seven decades.
The California Statewide Study of People Experiencing Homelessness (CASPEH), conducted by The University of California, San Francisco Benioff Homelessness and Housing Initiative (BHHI), is the largest representative study of homelessness in the United States since the mid-1990s. The study provides a comprehensive look at the causes and consequences of homelessness in California and recommends policy changes to shape programs in response. #CAHomelessnessStudy
Designed to be representative of all adults 18 years and older experiencing homelessness in California, CASPEH includes nearly 3,200 administered questionnaires and 365 in-depth interviews with adults experiencing homelessness in eight regions of the state, representing urban, rural, and suburban areas. Interviews were conducted in English and Spanish, with interpreters for other languages. In partnership with a wide array of community stakeholders, the UCSF BHHI team collected data between October 2021 and November 2022. CASPEH was funded by UCSF BHHI, the California Health Care Foundation, and Blue Shield of California Foundation.
Creative thinking improves while a person is walking and shortly thereafter, according to a study co-authored by Marily Oppezzo, a Stanford doctoral graduate in educational psychology, and Daniel Schwartz, a professor at Stanford Graduate School of Education.
The study found that walking indoors or outdoors similarly boosted creative inspiration. The act of walking itself, and not the environment, was the main factor. Across the board, creativity levels were consistently and significantly higher for those walking compared to those sitting.
Other research has focused on how aerobic exercise generally protects long-term cognitive function, but until now, there did not appear to be a study that specifically examined the effect of non-aerobic walking on the simultaneous creative generation of new ideas and then compared it against sitting, Oppezzo said.
Different combinations, such as two consecutive seated sessions, or a walking session followed by a seated one, were also compared. The walking or sitting sessions used to measure creativity lasted anywhere from 5 to 16 minutes, depending on the tasks being tested.
But not all thought processes are equal. While the study showed that walking benefited creative brainstorming, it did not have a positive effect on the kind of focused thinking required for single, correct answers.
The Federal Motor Carrier Safety Administration (FMCSA) and the National Highway Traffic Safety Administration (NHTSA) conducted the Large Truck Crash Causation Study (LTCCS) to examine the reasons for serious crashes involving large trucks (trucks with a gross vehicle weight rating over 10,000 pounds). From the 120,000 large truck crashes that occurred between April 2001 and December 2003, a nationally representative sample was selected. Each crash in the LTCCS sample involved at least one large truck and resulted in a fatality or injury.
The total LTCCS sample of 963 crashes involved 1,123 large trucks and 959 motor vehicles that were not large trucks. The 963 crashes resulted in 249 fatalities and 1,654 injuries. Of the 1,123 large trucks in the sample, 77 percent were tractors pulling a single semi-trailer, and 5 percent were trucks carrying hazardous materials. Of the 963 crashes in the sample, 73 percent involved a large truck colliding with at least one other vehicle.
Motor vehicle crashes are complex events. Usually they involve two or more vehicles. Elements that influence the occurrence of a crash may take place hours, days, or months before the crash. They include driver training and experience, vehicle design and manufacture, highway condition and traffic signaling, and weather conditions. Other elements may take place immediately before a crash, such as a decision to turn in traffic, a tire blowout, or snow. Crash reconstruction experts rarely conclude that crashes are the result of a single factor.
Fatigue, drinking alcohol, and speeding are major factors in motor vehicle crashes overall. Although their presence does not always result in a crash, these three factors, as well as other driver, vehicle, and environmental factors, can increase the risk that a crash will occur. In the LTCCS, 'causation' is defined in terms of the factors that are most likely to increase the risk that large trucks will be involved in serious crashes.
Data for the 963 crashes in the LTCCS sample were collected at 24 sites in 17 States. A crash researcher and a State truck inspector traveled to each crash site as soon as possible after the crash occurred. The researchers collected crash scene data through interviews with drivers, passengers, and witnesses, and the inspectors conducted thorough inspections of the trucks, the drivers' logbooks, and other documentation. After leaving the crash scene, the researchers collected additional data through interviews with motor carriers and, when the actual drivers could not be interviewed, surrogate drivers. The researchers also reviewed police crash reports, hospital records, and coroners' reports and revisited the crash scenes.
For each crash, data were collected on up to 1,000 elements, including the condition of the truck driver and the other drivers involved before the crash; the drivers' behavior during the crash; the condition of the trucks and other vehicles; roadway factors; and weather conditions. Data were coded by crash experts, difficult cases were reviewed by FMCSA and NHTSA staff, and completed cases were put into a publicly available electronic database on FMCSA's Web site.
According to NHTSA's estimate, there were approximately 120,000 fatal and injury crashes nationwide during the 33-month study period that involved at least one large truck; 141,000 large trucks were involved in those crashes. Each of the 963 LTCCS study cases was assigned a sampling weight, which allows for national estimates of total fatal and injury truck crashes during the study period.
All study results presented here are national estimates for the 141,000 large trucks that were estimated by NHTSA to have been involved in fatal and injury crashes during the study period. The estimates may differ from true values, because they are based on a probability sample of crashes and not a census of all crashes. The size of the difference may vary, depending on which LTCCS sample is the focus of a particular table or analysis.
Critical Event: The action or event that put the vehicle or vehicles on a course that made the collision unavoidable. The critical event is assigned to the vehicle that took the action that made the crash inevitable.
Critical Reason: The immediate reason for the critical event (i.e., the failure leading to the critical event). The critical reason is assigned to the vehicle coded with the critical event in the crash. It can be coded as a driver error, vehicle failure, or environmental condition (roadway or weather).
Associated Factors: The person, vehicle, and environmental conditions present at the time of the crash. No judgment is made as to whether any factor is related to the reason for a particular crash, just whether the factor was present. The list of the many factors that can be coded provides enough information to describe the circumstances of the crash.
Of the large trucks involved in all LTCCS crashes (single-vehicle and multi-vehicle), 55 percent were assigned the critical reason in crashes.
Of the large trucks involved in two-vehicle LTCCS crashes between one truck and one passenger vehicle (a car, van, pickup truck, or sport utility vehicle), 44 percent were assigned the critical reason.
Notes: Results shown are national estimates for the 141,000 large trucks estimated to have been involved in fatal and injury crashes during the study period. The estimates may differ from true values, because they are based on a probability sample of crashes and not a census of all crashes. Estimates are rounded to the nearest 1,000 large trucks.
Relative risk analysis of the data on associated factors, using the critical event and critical reason coding, allows the sorting out of factors into those merely present at the time of the crash and those that increase the risk of having a crash. The trucks involved in LTCCS crashes can be divided into two groups: those that were assigned the critical event and critical reason and those that were not. When the presence of associated factors coded to the two groups is compared, the relative risk of each factor can be assessed, as the following examples illustrate:
If 30 percent of the trucks assigned the critical reason for a crash were coded with the driver associated factor 'traveling too fast for conditions,' while only 5 percent of the trucks that were not assigned the critical reason were coded with the same associated factor, it can be concluded that speed is a factor that increases the risk of being involved in a crash.
If 30 percent of the trucks assigned the critical reason for a crash were coded with the driver associated factor 'prescription drug use,' while 30 percent of the trucks that were not assigned the critical reason were also coded with the same associated factor, it can be concluded that prescription drug use is not a factor that increases the risk of being involved in a crash.