Pedestrian Compliance at Signalized Intersections along Major Arterials

Background: Pedestrian non-compliance at signalized crossings is unsafe and considered one of the causes of pedestrian crashes. The speed limit on most major urban roads is 60 km/hr or less. However, the speed on some urban roads is higher in some countries. In this case, the situation is more unsafe and increases the possibility of fatal injuries or fatalities in the case of a crash. Therefore, it is expected that the pedestrians will be more cautious on these roads. Aim: This study aims to explore pedestrian compliance at signalized intersections on major arterials with 80 km/hr speeds in Qatar. Methods: Video data were collected for pedestrian movements at multiple intersections. Results: The study reported a 68.1 percent compliance rate at the study locations. The results also revealed that 14.6 percent of the pedestrians crossed during the Flashing Don’t Walk interval and 17.3 percent crossed during the Steady Don’t Walk interval. These rates are considered high compared to other countries. Several variables that may influence pedestrians’ behavior were investigated. Binary and ordinal logistic regression models were developed to describe the pedestrian crossing behavior as a function of these variables. Conclusion: Male and middle-age pedestrians were more likely to cross during these two intervals. The analysis showed that female pedestrians, elder pedestrians, pedestrians crossing in groups, pedestrians waiting before crossing, and pedestrians crossing against a flow of other pedestrians are more likely to comply and cross during the Walk interval compared to other groups. Several solutions were proposed in the study to increase compliance rates.

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Use of a Collar-Mounted Triaxial Accelerometer to Predict Speed and Gait in Dogs

Animals ◽

10.3390/ani11051262 ◽

2021 ◽

Vol 11 (5) ◽

pp. 1262

Author(s):

Samantha Bolton ◽

Nick Cave ◽

Naomi Cogger ◽

G. R. Colborne

Keyword(s):

Regression Models ◽

High Speed ◽

Video Data ◽

Accelerometer Data ◽

Triaxial Accelerometer ◽

Inherent Limitation ◽

Logistic Regression Models ◽

Accelerometer Signal ◽

Delta G ◽

Selection Of

Accelerometry has been used to measure treatment efficacy in dogs with osteoarthritis, although interpretation is difficult. Simplification of the output into speed or gait categories could simplify interpretation. We aimed to determine whether collar-mounted accelerometry could estimate the speed and categorise dogs’ gait on a treadmill. Eight Huntaway dogs were fitted with a triaxial accelerometer and then recorded using high-speed video on a treadmill at a slow and fast walk, trot, and canter. The accelerometer data (delta-G) was aligned with the video data and records of the treadmill speed and gait. Mixed linear and logistic regression models that included delta-G and a term accounting for the dogs’ skeletal sizes were used to predict speed and gait, respectively, from the accelerometer signal. Gait could be categorised (pseudo-R2 = 0.87) into binary categories of walking and faster (trot or canter), but not into the separate faster gaits. The estimation of speed above 3 m/s was inaccurate, though it is not clear whether that inaccuracy was due to the sampling frequency of the particular device, or whether that is an inherent limitation of collar-mounted accelerometers in dogs. Thus, collar-mounted accelerometry can reliably categorise dogs’ gaits into two categories, but finer gait descriptions or speed estimates require individual dog modelling and validation. Nonetheless, this accelerometry method could improve the use of accelerometry to detect treatment effects in osteoarthritis by allowing the selection of periods of activity that are most affected by treatment.

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Multinomial Logit Model of Pedestrian Crossing Behaviors at Signalized Intersections

Discrete Dynamics in Nature and Society ◽

10.1155/2013/172726 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 11

Author(s):

Zhu-Ping Zhou ◽

Ying-Shun Liu ◽

Wei Wang ◽

Yong Zhang

Keyword(s):

Latent Variables ◽

Logit Model ◽

Multinomial Logit Model ◽

Multinomial Logit ◽

Signalized Intersections ◽

Equation Modeling ◽

Survey Team ◽

Pedestrian Crashes ◽

Late Starters ◽

Pedestrian Crossing

Pedestrian crashes, making up a large proportion of road casualties, are more likely to occur at signalized intersections in China. This paper aims to study the different pedestrian behaviors of regular users, late starters, sneakers, and partial sneakers. Behavior information was observed manually in the field study. After that, the survey team distributed a questionnaire to the same participant who has been observed, to acquire detailed demographic and socioeconomic characteristics as well as attitude and preference indicators. Totally, 1878 pedestrians were surveyed at 16 signalized intersections in Nanjing. First, correlation analysis is performed to analyze each factor’s effect. Then, five latent variables including safety, conformity, comfort, flexibility, and fastness are obtained by structure equation modeling (SEM). Moreover, based on the results of SEM, a multinomial logit model with latent variables is developed to describe how the factors influence pedestrians’ behavior. Finally, some conclusions are drawn from the model: (1) for the choice of being late starters, arrival time, the presence of oncoming cars, and crosswalk length are the most important factors; (2) gender has the most significant effect on the pedestrians to be sneakers; and (3) age is the most important factor when pedestrians choose to be partial sneakers.

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Associations between Early-Life Food Deprivation and Risk of Frailty of Middle-Age and Elderly People: Evidence from the China Health and Retirement Longitudinal Study

Nutrients ◽

10.3390/nu13093066 ◽

2021 ◽

Vol 13 (9) ◽

pp. 3066

Author(s):

Chen Ye ◽

Sumiya Aihemaitijiang ◽

Ruoyu Wang ◽

Mairepaiti Halimulati ◽

Zhaofeng Zhang

Keyword(s):

Longitudinal Study ◽

Old Age ◽

Food Deprivation ◽

Regression Models ◽

Middle Age ◽

Later Life ◽

Logistic Regression Models ◽

Ordered Logistic Regression ◽

Loss Of Weight ◽

Increased Risk

Background: The association between childhood food deprivation (FD) and health in later life has been extensively studied; however, studies on the association between childhood food deprivation and frailty are scarce. This study assessed the associations between childhood FD and the risk of frailty at middle-age and old age. Methods: Three waves of the China Health and Retirement Longitudinal Study (CHARLS), including 11,615 individuals aged over 45 years, were used for this research. Frailty was operationalized according to the FRAIL scale as a sum of fatigue, resistance, ambulation, illness, and the loss of weight. Childhood FD experiences and levels were measured by self-reported FD and historical content. Logistic mixed-effects models and proportional odds ordered logistic regression models were used to analyse the association between childhood FD and frailty. Findings: Childhood FD increased the odds of frailty at old age (1.30, 95% CI: 1.26–1.36). Compared with subjects with mild FD, those with extreme FD experiences had increased risks of frailty (1.34, 95% CI: 1.26–1.43). Subjects exposed to hunger at different ages all had an increased risk of frailty, and subjects who had FD during ages 6–12 (1.15, 95% CI: 1.09–1.22) were more likely to have an increased risk of frailty than those who had experienced FD in younger ages. The interaction of experience of FD at ages 0–6 and the experience of FD at ages 6–12 is not statistically significant after adjusting all covariates. Conclusions: Our findings suggest that childhood FD exerts long-lasting effects on frailty among older adults in China. The prevention of childhood FD may delay or even avert the emergence of frailty in people of middle-age and old age.

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Religious Affiliation, Informal Participation, and Network Support Associated With Substance Use: Differences Across Age Groups

Health Education & Behavior ◽

10.1177/1090198119826259 ◽

2019 ◽

Vol 46 (4) ◽

pp. 656-665 ◽

Cited By ~ 3

Author(s):

Tuba Demir-Dagdas ◽

Stephanie T. Child

Keyword(s):

Substance Use ◽

Regression Models ◽

Middle Age ◽

Religious Affiliation ◽

Age Groups ◽

Religious Involvement ◽

Marijuana Use ◽

Logistic Regression Models ◽

Network Support ◽

Age Cohorts

Background. Associations between religious involvement and substance use are well established. However, limited research examines the effects of religious affiliation, informal participation, and network support on substance use among two distinct age cohorts. Objectives. This study aims to examine whether religious affiliation, informal participation, and network support are associated with alcohol, tobacco, and marijuana use among young and late middle-age adults. Method. The UC Berkeley Social Networks Study (Wave 1, 2015) offers novel cohort data on young (21-30 years old, n = 483) and late middle-age (50-70 years old, n = 673) adults. Poisson regression models were used to predict alcohol use, while logistic regression models were used to predict odds of smoking and marijuana use. Results. Among young adults, membership in a religious organization was associated with less alcohol, tobacco, and marijuana use. Conversely, participating in informal organizations was associated with more alcohol and marijuana use. Desiring more people to talk to and get together with were associated with more smoking and drinking, respectively. However, wishing more people to ask for help was associated with less substance use altogether. In a similar pattern, among older adults, religious involvement was associated with less alcohol and marijuana use. Desiring more people to ask for help was also related to less marijuana use. Conclusion. Younger adult participation in informal groups serves to encourage social substance use. In contrast, older people are more involved in religious groups, which support social behaviors that do not include substance use.

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Abstract P286: Sex-differences In The Prevalence Of Low Clinical Cardiovascular Health From Childhood To Middle-age

Circulation ◽

10.1161/circ.141.suppl_1.p286 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Author(s):

Liliana Aguayo ◽

Amy Krefman ◽

Orna Reges ◽

Matthew M Davis ◽

Darwin R Labarthe ◽

...

Keyword(s):

Sex Differences ◽

Regression Models ◽

Cardiovascular Health ◽

American Heart ◽

Middle Age ◽

Heart Association ◽

Primordial Prevention ◽

Logistic Regression Models ◽

Score Range

Introduction: This study examines sex differences in the prevalence of low clinical cardiovascular health (CVH) scores from ages 8-50 years old. Methods: Five cardiovascular cohorts (Bogalusa, Young Finns, HB!, CARDIA, and STRIP) were used to create a pooled cohort spanning from ages 8 to 50 years old. The American Heart Association criteria for poor, intermediate and ideal levels for 4 CVH factors (blood pressure, BMI, cholesterol, and glucose) were summed to calculate a clinical CVH score (range 0-8; higher being more ideal). Sex differences in the prevalence rates of low clinical CVH by age group (defined as a score ≤3) were estimated using logistic regression models. Results: Sex differences were examined among 9,386 participants with data on clinical CVH (56% female, 66% White and average follow-up time of 23 yrs). The prevalence of low clinical CVH increased for both men and women with age from 0.72% at age 8-14 yrs to 15% at 45-50 yrs of age in women and from 0.44% at ages 8-14 yrs to over 23% at ages 45-50 yrs in men. There were no significant sex differences in the prevalence of low clinical CVH at younger ages (8-20 years old, p>0.05). Between the ages of 21-26 years old, males were 2 times more likely to have low clinical CVH than women (odds ratio [OR] 2.2, 95% confidence interval [CI], 1.4-3.4). Sex differences in the prevalence of low clinical CVH persisted through adulthood and with only a slight decrease by ages 45-50 years old (OR 1.6, 95%CI 1.4-1.9). Conclusions: Sex differences in the prevalence of low clinical CVH change over the lifetime. In childhood the prevalence of low clinical CVH is similar. By young adulthood, men are more than twice more likely to have low clinical CVH than women; that sex difference is maintained throughout middle age. Understanding the reasons for the growing sex differences in the prevalence of low clinical CVH with age may help to identify targets for primordial prevention, especially prevention strategies to target young men.

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Smoking, distress and COVID-19 in England: cross-sectional population surveys from 2016 to 2020

10.1101/2020.12.07.20245514 ◽

2020 ◽

Author(s):

Loren Kock ◽

Lion Shahab ◽

Jamie Brown ◽

Graham Moore ◽

Marie Horton ◽

...

Keyword(s):

Psychological Distress ◽

Regression Models ◽

Mental Health Problems ◽

Middle Age ◽

Age Groups ◽

Cross Sectional ◽

Logistic Regression Models ◽

Time Period ◽

Chi Squared ◽

Logistic Regressions

Background: Changes in the prevalence of mental health problems among smokers due to the COVID-19 pandemic in England have important implications for existing health inequalities. This study examined the prevalence of psychological distress among smokers following the onset of the pandemic compared with previous years. Methods: Cross-sectional data were used from a representative survey of smokers (18+) in England (n = 2,927) during four months (April to July) in 2016, 2017 and 2020. Adjusted logistic regressions estimated the associations between past-month psychological distress across two time periods (2016/17 and 2020), and age. Weighted proportions, chi-squared statistics and stratified logistic regression models were used to compare the distributions of minimal, moderate and severe distress, respectively, within socio-demographic and smoking characteristic categories in 2016/17 and 2020. Results: The prevalence of moderate and severe distress among past-year smokers was higher in 2020 (moderate: 28.79%, 95%CI 26.11-31.60; OR=2.08, 95%CI 1.34-3.25; severe: 11.04%, 9.30-13.12; OR=2.16, 1.13-4.07) than in 2016/17 (moderate: 20.66%, 19.02-22.43; severe: 8.23%, 7.16-9.47). While there was no overall evidence of an interaction between time period and age, young (16-24 years) and middle-age groups (45-54 years) may have experienced greater increases in moderate and older age groups (65+ years) in severe distress from 2016/17 to 2020. There were also increases in 2020 of moderate distress among those from more disadvantaged social grades and of both moderate and severe distress among women and those with low cigarette addiction. Conclusions: Between April-July 2016/17 and April-July 2020 in England there were increases in both moderate and severe distress among smokers. The distribution of distress differed between 2016/17 and 2020 and represents a widening of established inequalities, with increases in distress among socio-economically disadvantaged groups, women and diverging age groups.

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Assessing damage severity of plant hopper and leaf folder in rice using hyperspectral remote sensing and multinomial logistic regression models

10.1603/ice.2016.93420 ◽

2016 ◽

Author(s):

Mathyam Prabhakar

Keyword(s):

Remote Sensing ◽

Logistic Regression ◽

Regression Models ◽

Multinomial Logistic Regression ◽

Hyperspectral Remote Sensing ◽

Logistic Regression Models

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The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

Journal of Cancer Science and Therapeutics ◽

10.36879/jcst.19.000109 ◽

2019 ◽

pp. 1-5

Keyword(s):

Decision Making ◽

Logistic Regression ◽

Skin Necrosis ◽

Regression Models ◽

Multivariable Analysis ◽

P Value ◽

Flap Necrosis ◽

Single Institution ◽

Logistic Regression Models ◽

The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

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Demographic factors associated with missed follow-up among solid tumor patients treated at a large multi-site academic institution

Future Oncology ◽

10.2217/fon-2020-0425 ◽

2020 ◽

Vol 16 (32) ◽

pp. 2635-2643

Author(s):

Samantha L Freije ◽

Jordan A Holmes ◽

Saleh Rachidi ◽

Susannah G Ellsworth ◽

Richard C Zellars ◽

...

Keyword(s):

Cancer Patients ◽

Odds Ratio ◽

Regression Models ◽

Tumor Patients ◽

Logistic Regression Models ◽

Factors Associated ◽

Follow Up Care ◽

Risk Patients ◽

African American Race

Aim: To identify demographic predictors of patients who miss oncology follow-up, considering that missed follow-up has not been well studies in cancer patients. Methods: Patients with solid tumors diagnosed from 2007 to 2016 were analyzed (n = 16,080). Univariate and multivariable logistic regression models were constructed to examine predictors of missed follow-up. Results: Our study revealed that 21.2% of patients missed ≥1 follow-up appointment. African–American race (odds ratio [OR] 1.33; 95% CI: 1.17–1.51), Medicaid insurance (OR 1.59; 1.36–1.87), no insurance (OR 1.66; 1.32–2.10) and rural residence (OR 1.78; 1.49–2.13) were associated with missed follow-up. Conclusion: Many cancer patients miss follow-up, and inadequate follow-up may influence cancer outcomes. Further research is needed on how to address disparities in follow-up care in high-risk patients.

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