The Contribution of Socio-Demographic Factors to Walking Behavior Considering Destination Types; Case Study: Temuco, Chile

The improvement of walking contributes to maintain the minimum rate of physical activity and therefore the residents’ public health. This is while the amount of walking in daily transport of inhabitants has significantly decreased during the last decades in Temuco, Chile. In addition, the impact of socio-demographic as well as social factors on the improvement of walking behavior has been paid less attention in previous studies. This study aims to examine the contribution of socio-demographic factors and the active family environment to walking behavior as well as walking level based on three types of destinations in Temuco. The results of “Encuesta Origin Destino” (EOD) in Temuco were used to examine the objectives. It was found that a high percentage of people who walk in Temuco belong to low-income families. Moreover, most of the people who walk, do not have a driver’s license nor private cars in their household. Certain socio-demographic factors such as age, gender, driver’s license, private cars, and access to TV were found to have associations with overall walking behavior as well as walking level depending on three different destination types. Furthermore, the correlation was found between walking behavior and active family environment. These findings were discussed and their implications were addressed as well.

Gender-Specific Impact of Self-Monitoring and Social Norm Information on Walking Behavior Among Chinese College Students Assessed Using WeChat: Longitudinal Tracking Study

Background Walking is a simple but beneficial form of physical activity (PA). Self-monitoring and providing information about social norms are the 2 most widely used “mobile health (mHealth)” strategies to promote walking behavior. However, previous studies have failed to discriminate the effect of self-monitoring from the combination of the 2 strategies, and provide practical evidence within Chinese culture. Some essential moderators, such as gender and group identity, were also overlooked. Objective We aimed to investigate the effectiveness of social norm and self-monitoring interventions for walking behavior and assess the moderating effects of gender and group identity, which could guide optimal mHealth intervention projects in China. Methods In 2 longitudinal tracking studies (study 1, 22 days; study 2, 31 days), Chinese college students wore trackers for at least 8 hours per day (MASAI 3D Pedometer and Xiaomi Wristband 2) to record their daily step counts in baseline, intervention, and follow-up stages. In each study, participants (study 1: n=117, 54% female, mean age 25.60 years; study 2: n=180, 51% female, mean age 22.60 years) were randomly allocated to 1 of the following 3 groups: a self-monitoring group and 2 social norm intervention groups. In the 2 intervention groups and during the intervention stage, participants received different social norm information regarding group member step rankings corresponding to their grouping type of social norm information. In study 1, participants were grouped by within-group member PA levels (PA consistent vs PA inconsistent), and in study 2, participants were grouped by their received gender-specific social norm information (gender consistent vs gender inconsistent). Piece-wise linear mixed models were used to compare the difference in walking steps between groups. Results In study 1, for males in the self-monitoring group, walking steps significantly decreased from the baseline stage to the intervention stage (change in slope=−1422.16; P=.02). However, additional social norm information regardless of group consistency kept their walking unchanged. For females, social norm information did not provide any extra benefit beyond self-monitoring. Females exposed to PA-inconsistent social norm information even walked less (slope during the intervention=−122.18; P=.03). In study 2, for males, a similar pattern was observed, with a decrease in walking steps in the self-monitoring group (change in slope=−151.33; P=.08), but there was no decrease in the 2 social norm intervention groups. However, for females, gender-consistent social norm information decreased walking steps (slope during the intervention=−143.68; P=.03). Conclusions Both gender and group identity moderated the effect of social norm information on walking. Among females, social norm information showed no benefit for walking behavior and may have exerted a backfire effect. Among males, while walking behavior decreased with self-monitoring only, the inclusion of social norm information held the level of walking behavior steady.

Behavioral-Based Pedestrian Modeling Approach: Formulation, Sensitivity Analysis, and Calibration

Pedestrians are among the travelers most vulnerable to collisions that are associated with high fatality and injury rates. The increasing rate of urbanization and mixed land-use construction make walking (along with other non-motorized travel) a predominant transportation mode with a wide variety of behaviors expected. Because of the inherent safety concerns seen in pedestrian transportation infrastructures, especially those with conflicting multimodal movements expected (crosswalks, transit platforms, etc.), it is important that pedestrian behavior is modeled as a risk-taking stochastic behavior that may lead to errors and thus collision formation. In previous work, the complexity and cost associated with building pedestrian models in a cognitive-based environment weighted down the construction of simulation tools that can capture pedestrian-involved collisions, including those seen in shared space environments. In this paper, a tool that will help evaluate the safety of pedestrian traffic is initiated: an extended modeling framework of pedestrian walking behavior is adopted while incorporating different physiological, physical, and decision-making elements. The focus is on operational decisions (i.e., path choices defined by longitudinal and lateral trajectories) with a pre-specified set of origins and destinations. The model relies on the prospect theory paradigm where pedestrians evaluate their acceleration and directional alternatives while considering the possibility of colliding with other “particles.” Using a genetic algorithm method, the new model is calibrated using detailed trajectory data. This model can be extended to model the interactions between a variety of different modes that are present in different mixed land-use environments.

Promoting the adoption of behaviors to prevent osteoporosis using the health belief model integrated with health literacy: quasi-experimental intervention study

Background The health belief model (HBM) is effective in preventing osteoporosis and promoting health literacy (HL). In this regard, there are some critical points such as the role of HL in preventing osteoporosis, adoption of preventive behaviors, adoption of behaviors, including physical activity, and the role of health volunteers in transmitting health messages to the community. Considering the aforesaid points this study was performed among the health volunteers aimed to determine the effect of educational intervention based on integrated HBM with HL on walking and nutrition behaviors to prevent osteoporosis. Materials and methods In this quasi-experimental intervention study, 140 health volunteers (70 people in each of the two intervention and control groups) were enrolled in the study using multi-stage random sampling, in 2020. The members of the intervention group received e-learning through social media software, 4 times during 4 weeks (once a week) and were provided with educational booklets and pamphlets. Data collection tools included demographic and background questionnaires; standard questionnaire based on the HBM, awareness, and walking and nutrition behaviors to prevent osteoporosis; and HELIA questionnaire to measure HL. These questionnaires were completed in two stages, before and 3 months after the intervention. The educational intervention in this study was sent to the intervention group in 4 stages. The collected data were analyzed using proportional tests (paired t-test, Wilcoxon test, independent t-test, Mann-Whitney test) and SPSS software version 23. Results The mean and standard deviation related to the score of adoption of nutrition behaviors at the beginning of the study in the intervention group was 5.398 ± 1.447, which changed to 8.446 ± 1.244 after 3 months, indicating a significant increase in the adoption of such behaviors (P = 0.009). In the control group, the mean and standard deviation of the scores of adoption of nutrition behaviors changed from 5.451 ± 1.222 to 6.003 ± 1.005, which was not statistically significant (P = 0.351). Also, the mean and standard deviation related to the scores of adoption of walking behavior at the beginning of the study in the intervention group was 8.956 ± 0.261, which changed to 13.457 ± 0.587 after 3 months, indicating a significant increase in the adoption of such behaviors (P < 0.001). In the control group, the mean and standard deviation related to the scores of the adoption of walking behavior changed from 8.848 ± 0.353 to 9.025 ± 0.545, which was not statistically significant (P = 0.211). Prior to the intervention, there was no significant difference between two groups regarding the variables of demographic and background, knowledge, all constructs of the model, HL, and adoption of walking and nutrition behaviors (P > 0.05). After the intervention, the comparison of the two groups showed that there was a significant change in the mean scores of awareness, all constructs of the model, HL, and adoption of preventive behaviors in the intervention group than the control group (P < 0.05). Conclusion The educational intervention based on an HBM integrated with HL was effective and acceptable in correcting and promoting walking and nutrition behaviors to prevent osteoporosis among health volunteers. Therefore, it can be said that the intervention implemented was in line with the developed model used.

Further Analysis of the Passive Dynamics of the Compass Biped Walker and Control of Chaos via Two Trajectory Tracking Approaches

This work consists in analyzing and controlling the walk of the compass-type bipedal walker in order to stabilize its passive dynamic gait. The dynamic walking of the compass-gait walker is modeled by an impulsive hybrid nonlinear system. This impulsive hybrid nature is considered very complex as it can generate unwanted phenomena such as chaos and bifurcations. We show first by means of bifurcation diagrams and by varying the slope angle of the walking surface and also the length of the lower leg segment that the passive dynamic walking exhibits successive period-doubling bifurcations leading to chaos. Furthermore, in order to control chaos and hence obtain one-periodic walking behavior, we propose two control approaches based on tracking a desired trajectory. The first method consists in tracking the one-periodic passive dynamic walking generated by the compass model itself. The second control method lies in following a planned trajectory using the 4th-order Spline function. An optimization method is also achieved to design the parameters of the desired trajectory. Some features of the period-1 passive gait are used in the design of such Spline trajectory. Finally, we show some simulation results revealing the efficiency of the two proposed control methods in the control of the chaotic passive gait of the compass-gait walker. Moreover, we demonstrate the stabilization of the bipedal locomotion of the compass biped walker on different slopes: descending and ascending inclined planes and walking on a level ground. A comparison with the OGY-based control method is also performed to further show the superiority of these two control approaches.

Intranasal oxytocin treatment on the day of weaning does not decrease walking behavior or improve plasma metabolites in beef calves placed on pasture

The purpose of this study was to evaluate the effect that intranasal oxytocin administered at abrupt weaning (day 0) had on weaning stress behaviors such as walking distance and time devoted to walking, calf body weight, and plasma non-esterified fatty acids (NEFA), β-hydroxybutyrate (β-HB), and cortisol. Twenty Simmental × Angus heifer calves were randomly assigned to one of two treatments, intranasal oxytocin (OXT; n = 10) or intranasal saline (CON; n = 10). All calves were given the respective intranasal treatment on the day of weaning (day 0), and then placed on pasture together. Calves were weighed and a blood sample was obtained on days 0, 1, 7, and 14 post-weaning. Blood samples were subsequently used to quantify plasma NEFA, β-HB, and cortisol concentrations. All calves in both treatment groups were fitted with an individual global positioning system (GPS) that recorded calf location every ten seconds for a 16 hour period on days 0, 7, and 14 to quantify and evaluate walking behaviors. There was no treatment × day effect for distance walked (P = 0.82), walking time (P = 0.80), non-walking time (P = 0.88), area utilization index (P = 0.84), calf body weight (P = 0.82), average daily gain (P = 0.54), NEFA (P = 0.22), or cortisol concentrations (P = 0.32). There was a tendency for a treatment × day effect observed for average walking speed (P = 0.09) and β-HB (P = 0.10), such that calves in the CON treatment tended to have lesser average walking speeds on day 14 and tended to have greater β-HB concentration after weaning. There was a treatment effect (P = 0.02) for NEFA concentrations, with the CON calves having a greater plasma NEFA concentration throughout the study compared with OXT calves. These data imply that OXT calves may have had differing metabolic responses immediately after weaning that could have altered the mobilization of NEFA, but this change was not substantial enough to impact body weights or walking behaviors.

Spatially Varying Effects of Street Greenery on Walking Time of Older Adults

Population aging has become a notable and enduring demographic phenomenon worldwide. Older adults’ walking behavior is determined by many factors, such as socioeconomic attributes and the built environment. Although a handful of recent studies have examined the influence of street greenery (a built environment variable readily estimated by big data) on older adults’ walking behavior, they have not focused on the spatial heterogeneity in the influence. To this end, this study extracts the socioeconomic and walking behavior data from the Travel Characteristic Survey 2011 of Hong Kong and estimates street greenery (the green view index) based on Google Street View imagery. It then develops global models (linear regression and Box–Cox transformed models) and local models (geographically weighted regression models) to scrutinize the average (global) and location-specific (local) relationships, respectively, between street greenery and older adults’ walking time. Notably, green view indices in three neighborhoods with different sizes are estimated for robustness checks. The results show that (1) street greenery has consistent and significant effects on walking time; (2) the influence of street greenery varies across space—specifically, it is greater in the suburban area; and (3) the performance of different green view indices is highly consistent.

A Theoretical Analysis of the Pricing and Advertising Strategies with Lévy-Walking Consumers

The pervasive adoption of mobile devices and proximity technologies enables firms to trace consumers’ trajectories and locations. This connects firms’ marketing and operations strategies more tightly with consumer mobility. In this paper, we propose a novel analytical model to examine the economic effects of consumer mobility on pricing and advertising strategies by incorporating consumers’ Lévy-walking behavior into advertising economics models. We ascertain the convergent effect of consumer mobility, i.e., consumers’ convergence to a firm leads to higher product price and advertising level. Meanwhile, it improves social welfare by increasing firm profit and consumer surplus. More interestingly, we find that consumers’ average movement distance (AMD) has opposing influences in pricing and advertising strategies. Specifically, longer AMD strengthens the convergent effect on advertising strategy but weakens that on pricing strategy. Finally, we also conduct a numerical analysis to uncover the impacts of the presence of proximity technologies on advertising outcomes. The results of this paper provide advisable guidance to firms on how to craft and adjust pricing and advertising strategies in accordance to consumer mobility. Moreover, the results present insights on welfare implications of informative advertising from the perspective of consumer mobility.

Non-linear Relationships Between the Built Environment and Walking Frequency Among Older Adults in Zhongshan, China

Aim: Promoting walking activity is an effective way to improve the health of older adults. Walking frequency is a critical component of walking behavior and an essential determinant of daily walking levels. To decipher the association between the built environment and walking frequency among older adults, this study's aims are as follows: (1) to empirically test whether non-linear relationships between the two exist, and (2) to identify the thresholds of the built environment characteristics that promote walking.Methods: The walking frequency of old adults was derived from the Zhongshan Household Travel Survey (ZHTS) in 2012. The sample size of old adults aged 60 or over was 4784 from 274 urban and rural neighborhoods. A semi-parametric generalized additive model (GAMM) is used to analyze the non-linear or non-monotonic relationships between the built environment and the walking frequency among older adults.Results: We found that non-linear relationships exist among five out of the six built environment characteristics. Within certain thresholds, the population density, sidewalk density, bus stop density, land use mixture, and the percentage of green space are positively related to older adults' walking trips. Furthermore, the land use mixture and the percentage of green space show an inverse “V”-shaped relationship.Conclusions: Built environment features can either support or hinder the walking frequency among older adults. The findings in the current study contribute to effective land use and transport policies for promoting active travel among older adults.