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Background: Lifestyle changes are important for the prevention and management of metabolic syndrome (MetS), but studies that focus on gender differences in the lifestyle risk factors of MetS are limited in China. This research aimed to generate a healthy lifestyle index (HLI) to assess the behavioral risk factors of MetS and its components, and to explore the gender differences in HLI score and other influencing factors of MetS. Methods: A convenience sample of 532 outpatients were recruited from a general hospital in Changsha, China. The general information and HLI scores [including physical activity (PA), diet, smoking, alcohol use, and body mass index (BMI)] of the subjects were collected through questionnaires, and each patient's height, weight, waist circumference, and other physical signs were measured. Logistic regression analysis was used to analyze the risk factors of MetS and its components. Results: The prevalence of MetS was 33.3% for the whole sample (46.3% in males and 23.3% in females). The risk of MetS increased with age, smoking, unhealthy diet, and BMI in males and with age and BMI in females. Our logistic regression analysis showed that lower HLI (male: OR = 0.838,95%CI = 0.757–0.929; female: OR = 0.752, 95%CI = 0.645–0.876) and older age (male: OR = 2.899, 95%CI = 1.446–5.812; female: OR = 4.430, 95%CI = 1.640–11.969) were independent risk factors of MetS, for both sexes. Conclusion: Low levels of HLI and older ages were independent risk factors of MetS in both males and females. The association between aging and MetS risk was stronger in females, while the association between unhealthy lifestyles and MetS risk was stronger in males. Our findings reinforced the expected gender differences in MetS prevalence and its risk factors, which has implications for the future development of gender-specific MetS prevention and intervention programs. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the unsafe conditions of pedestrian crossings at signalized intersections under the mixed traffic environment in Changsha, China. For this purpose, based really pedestrian-related crash data of Changsha city and visualized crash geographic information, six typical urban signalized intersections were selected. The peak and off-peak surveillance videos of six signalized intersections were collected via field surveys, 1,070 conflicts were extracted through using professional trajectory tracking software Traker to track pedestrian and vehicle trajectories. PSMT (Pedestrian Safety Margin Time) was used as an indicator to identify the severity of conflicts, and manually recorded the characteristics of pedestrian crossing behavior, vehicles and roads during the conflict. An Ordered Probit model was established to analyze the risk factors that led to different severities of the conflict between pedestrians and vehicles. The model outcome indicates a significant relationship between the severity level and characteristics of pedestrian behavior, vehicles and conflict. Moreover, it was identified that, in addition to the above characteristics, roadway characteristics significantly influenced likelihood of severe pedestrian-vehicle conflict. Finally, these factors are discussed, and suggestions for improving the pedestrian traffic environment are proposed from different perspectives. [ABSTRACT FROM AUTHOR]