Effect of commuting on the risk of COVID-19 and COVID-19-induced anxiety in Japan, December 2020

Background To prevent the spread of coronavirus disease (COVID-19), it is important to avoid 3Cs (closed spaces, crowded places, and close-contact settings). However, the risk of contact with an unspecified number of people is inevitable while commuting to and from work. In this study, we investigated the relationship between commuting, and the risk of COVID-19 and COVID-19-induced anxiety. Methods An internet-based questionnaire survey was conducted to obtain a dataset from 27,036 respondents. One-way commuting time was evaluated using a five-case method. The commuting distance was estimated using zip codes of the home and workplace. Logistic regression analysis was performed with the following outcomes: COVID-19 risk, close contact, infection anxiety, and infection anxiety due to commuting. Commuting distance and commuting time were analyzed separately in the model. We excluded participants with incalculable commuting distance, commuting distance exceeding 300 km, commuting distance of 0 km, or who telecommuted at least once a week. Results The total number of participants included in the analysis was 14,038. The adjusted odds ratios (aORs) of using public transportation for severe acute respiratory syndrome coronavirus 2 infection were 4.17 (95% confidence interval [CI]: 2.51–6.93) (commuting time) and 5.18 (95% CI: 3.06–8.78) (commuting distance). The aOR of COVID-19 diagnosis decreased significantly with increasing commuting distance. The aORs of using public transportation to infection anxiety were 1.44 (95% CI: 1.31–1.59) (commuting time) and 1.45 (95% CI: 1.32–1.60) (commuting distance). The longer the commuting time, the more the aOR increased. Conclusions COVID-19 risk, close contact, and infection anxiety were all associated with the use of public transportation during commuting. Both commuting distance and time were associated with infection anxiety due to commuting, and the strength of the association increased with increase in commuting time distance. Since transportation by commuting is associated with COVID-19 risk and anxiety, we recommend the use of telecommuting and other means of work.

Physical inactivity, and its association with hypertension among employees in the district of Colombo

Background Physical inactivity is a leading cause of morbidity and mortality and is a major public health problem. Insufficient activity is responsible for a large proportion of non-communicable diseases such as hypertension. Objectives The purpose of this study was to assess socioeconomic variations in physical activity and to measure the association between physical inactivity and hypertension among government officials in Sri Lanka. Methods A cross-sectional study was carried out among 275 senior-officers(SOs) and 760 managerial-assistants(MAs) aged 30–60 years and attached to Public Administration institutions in Colombo District in Sri Lanka. Physical-activity(PA) was gathered using the International Physical Activity Questionnaire(IPAQ) adopted and validated to the Sri Lankan context. Blood pressure(measured and classified using JNC-7 guidelines) and anthropometric indices were recorded. Energy utilization of all vigorous and moderated PA and walking was expressed as metabolic-equivalent-of-task(MET) min per week. A total-MET-score was calculated and categorized based on IPAQ guidelines. Results Socioeconomic variations in PA levels were observed as 58.1%(n = 158) SOs and 30.6%(n = 226) MAs were involved in inadequate PA. Among the SOs diagnosed with hypertension, more half(59.1%; n = 52) were physically inactive, while among MAs, 65.9%(n = 143) with hypertension were physically inactive. After adjusting for potential confounding factors being physically inactive was associated with a higher risk of hypertension among SOs[OR 2.08 [95% CI 1.07, 4.6] and MAs[OR 2.8 [95% CI 1.8, 4.6]. The main modality of commuting to work for SOs(59%) was private transport, and MAs(64%) public transport Commuting distance was positively correlated(p < 0.05) with total transport MET among SOs and MAs. After adjusting for confounders, commuting distance of > 20 km was found to lower the odds of hypertension among SOs and MAs(OR = 0.713; 95% CI 0.4 to1.3; and OR = 0.63; 95% CI 0.46 to 0.87). Conclusion Despite the current knowledge that being physically active promotes health, the practice was different. Physical inactivity was associated with hypertension and prevalent among both SOs and MAs. Higher commuting distance is positively correlated with total transport MET and associated with lower odds of hypertension among SOs and MAs. Longitudinal studies are required to provide a causative association between physical inactivity and hypertension among these employees.

The Relations between Street Network Configuration and Travel Behavior in Pakistan; the Optimal Level of Street Connectivity for a More Active Mobility

Urban sprawl is a particular pattern of the street network and land use. The relationship between street networks and sprawl has been discussed by urban scholars in developed and high-income countries. Nevertheless, there is a lack of research on the relationships between street connectivity and urban travel behavior, particularly among emerging markets. This paper aims to study correlations between urban mobility and street-length density as an indicator for assessing the compactness of an area by developing two hierarchical regression models and controlling for socioeconomic variables in two large Pakistani cities: Lahore and Rawalpindi. Moreover, this paper defines optimal cutoff values for street-length density and active transport. Finally, three chi-square tests were conducted to assess the differences between using different mode choices by people living in sprawled neighborhoods versus compact neighborhoods. Our findings confirm the use of different transport modes depending on the purpose of the trip (commuting or non-commuting), length of trip (within or outside the neighborhood), and starting point (sprawled neighborhood or compact area). We also find a positive correlation between street-length density around homes and commuting distance, the frequency of public transport use, and the use of private motor vehicles in commuting trips in the two cities. Street-length density around workplaces is correlated with commuting distance, the frequency of public transport use, and the use of private motor vehicles when socioeconomic variables (including age, daily activity, and monthly income) are controlled for in the two models. The behavior of Pakistani residents changes with a street-length density of 137 and 144.7 m/m2 for homes and workplaces, respectively, in terms of using active mobility.

Universal patterns of long-distance commuting and social assortativity in cities

Millions commute to work every day in cities and interact with colleagues, partners, friends, and strangers. Commuting facilitates the mixing of people from distant and diverse neighborhoods, but whether this has an imprint on social inclusion or instead, connections remain assortative is less explored. In this paper, we aim to better understand income sorting in social networks inside cities and investigate how commuting distance conditions the online social ties of Twitter users in the 50 largest metropolitan areas of the United States. An above-median commuting distance in cities is linked to more diverse individual networks, moreover, we find that longer commutes are associated with a nearly uniform, moderate reduction of overall social tie assortativity across all cities. This suggests a universal relation between long-distance commutes and the integration of social networks. Our results inform policy that facilitating access across distant neighborhoods can advance the social inclusion of low-income groups.

Research on the Impact of the Built Environment on the Characteristics of Metropolis Rail Transit School Commuting—Take Wuhan as an Example

The long-distance commute to school caused by urban sprawl and the car-oriented urban construction model are key factors leading to primary/middle school students being picked up by their parents in cars. Encouraging those students to take rail transit can reduce their dependence on cars. This paper uses a stepwise regression based on rail-transit swipe data to explore the influence of the built environment on rail-transit commuting characteristics in Wuhan, and uses a geographically weighted regression (GWR) model to analyze the spatial heterogeneity of significant influencing variables. The study found that: (1) 60% of students are one-way commuters; (2) 88.6% of students travel less than 10 km; (3) the floor area ratio, bus station density and whether the station is a transfer station have an obvious positive effect on the flow of commuters; (4) whether the station is a departure station has a positive effect on the commuting distance, but the mixed degree of land use and road density have a negative effect on the commuting distance. This research can assist cities in formulating built environment optimization measures and related policies to improve school-age children’s use of rail transit. This is important in the development of child-friendly cities.

Optimal Excess Commuting Evaluation Based on Local Minimal Costs

Excess commuting refers to the value of unnecessary commuting or distance costs. Traditional commuting distance models adapt the most efficient scenario with people working in the nearest workplace geographically. Even though there have been some attempts to include constraints with commuter attributes and neighborhood features, problems arise with traditional geographical space and the subjectivity of these predefined characteristics. In this paper, we propose a method to calculate theoretical local minimal costs, which considers preferences that are inherently behavioral based on current work–home trips in the process of reassigning the work–home configuration. Our method is based on a feature space with a higher dimension and with the enlargement of attributes and relations of and between commuters and neighborhoods. Additionally, our solution is arrived at innovatively by improved Fuzzy C-Means clustering and linear programming. Unlike traditional clustering algorithms, our improved method adapts entropy information and selects the initial parameters based on the actual data rather than on prior knowledge. Using the real origin–destination matrix, theoretical minimal costs are calculated within each cluster, referred to as local minimal costs, and the average sum of local minimal costs is our theoretical minimal cost. The difference between the expected minimal cost and the actual cost is the excess commuting. Using our method, experimental results show that only 13% of the daily commuting distance in Wuhan could be avoided, and the theoretical distance is approximately 1.06 km shorter than the actual commuting distance.

Physical Inactivity, and Its Association with Hypertension Among Employees in the District of Colombo

Background: Physical inactivity is a leading cause of morbidity and mortality and is a major public health problem. Insufficient activity is responsible for a large proportion of non-communicable diseases such as hypertensionObjectives: The purpose of this study was to assess socio-economic variations in physical activity and to measure the association between physical-inactivity and hypertension among government officials in Sri Lanka.Methods: A cross-sectional study was carried out among 275 senior-officers(SOs) and 760 managerial-assistants(MAs) aged 30-60 years and attached to Public Administration institutions in Colombo District in Sri Lanka. Physical-activity(PA) was gathered using the International Physical Activity Questionnaire(IPAQ) adopted and validated to the Sri Lankan context. Blood pressure(measured and classified using JNC-7 guidelines), and anthropometric indices were recorded. Energy utilization of all vigorous and moderated PA and walking was expressed as metabolic-equivalent-of-task(MET) min per week. A total MET score was calculated and categorized based on IPAQ guidelines. Results: Socio-economic variations in PA levels were observed as 58.1%(n=158) SOs and 30.6%(n=226) MAs were involved in inadequate PA. Of the diagnosed hypertensives, 44.7%(n=106), and 49.4%(n=117) reported a low and moderate PA and considering non-hypertensives, 35.9%(n=278), 57.5%(n=445) reported a low and moderate activity levels respectively. After adjusting for potential confounding factors being physically inactive was associated with a higher risk of hypertension[Odds rate ratio(OR) 1.33[95% CI 1.07, 1,65], indicating that physical-inactivity increased the risk of hypertension by 30%. The main modality of commuting to work for SOs(59%) was private transport, and MAs(64%) public transport Commuting distance was positively correlated(p<0.05) with total transport MET among SOs and MAs. After adjusting, commuting distance of >20 km was associated with lower odds of hypertension among SOs and MAs(OR=0.713; 95% CI 0.4 to1.3; and OR=0.63; 95% CI 0.46 to 0.87).Conclusion: Despite the current knowledge that being physically active promotes health, the practice was different. Physical inactivity was associated with hypertension and prevalent among both SOs and MAs. Higher commuting distance is positively correlated with total transport MET and associated with lower odds of hypertension among SOs and MAs. Longitudinal studies are required to provide a causative association between physical inactivity and hypertension among these employees.