Many aspects of presenteeism still warrant caution, especially when using presenteeism measurements to quantify economic outcomes. Focusing on productivity at the population level, rather than the individual level, may be more appropriate.

Quantifiable life-cycle models of the service life of pavement markings are essential for a cost-efficient pavement marking management system. A study was conducted to develop an analysis procedure for typical pavement marking retroreflectivity inspection data. Retroreflectivity data collected by the National Transportation Product Evaluation Program on water-based paints in 2002 on a Pennsylvania test deck were used. Those data were considered interval-level duration data, and a Weibull analysis was performed. A Weibull analysis is a typical method in reliability engineering in which Weibull scale and shape parameters are estimated from failure data for making objective maintenance decisions. Results of the Weibull analysis indicated that the water-based paints had shape and scale parameters of 1.42 (±0.05), and 601.67 (±17.73) days, respectively, for skip line areas and 2.38 (±0.08) and 227.41 (±4.48) days, respectively, for left wheelpath areas. It was also determined that the probability of 2-year water-based paints lasting above 100 mcd/m2/lx varied from 0% to 27%. The lower limit corresponds to the left wheelpath, and the upper limit corresponds to the skip line area. The left wheelpath markings failed to stay above 100 mcd/m2/lx after approximately a year, while skip line markings could maintain 100 mcd/m2/lx ratings or higher for more than 1,000 days. White markings were found to last longer than yellow markings for the same exposure. This study used data from a single site in Pennsylvania. A multisite analysis accounting for time and space variations is recommended before adopting this method for minimum pavement marking retroreflectivity standard assessment.

Pavement markings provide useful visual and navigational guidance information to motorists. Current warrants for the application of pavement markings in the United States are based on traffic volume, traveled way width, and number of travel lanes. To be effective, pavement markings must be visible to drivers, particularly at night. The purpose of this paper is to perform an exploratory analysis to determine if a relationship between pavement marking retroreflectivity and crash frequency exists. First, models of pavement marking retroreflectivity degradation were developed from selected highways in North Carolina using artificial neural networks. Monthly estimates of pavement marking retro-reflectivity levels were then appended to roadway inventory and crash frequency data. Generalized estimating equations were used to estimate the monthly target crash frequency. The results indicate that the regression parameter estimates for yellow and white edgeline pavement markings were negative, but neither was statistically significant for the two-lane highway nighttime target crash frequency model. For multilane highways, all of the pavement marking retro-reflectivity parameter estimates were statistically significant. The white pavement marking retroreflectivity parameter estimates were negative, as expected. The yellow pavement marking retroreflectivity parameter estimate was positive.

Communities do have a modest association with SRH of the employees living there. After adjusting for individual-level and demographic variables, employees living in less/moderately deprived communities are more likely to perceive better physical health relative to those who live in highly deprived communities.