The effect of fine particulate matter (PM2.5) pollution on health inequality: an intergenerational perspective.

Air pollution poses a serious challenge to public health and simultaneously exacerbating regional & intergenerational health inequality. This research introduces PM2.5 pollution into the intergenerational health transmission model, and estimates its impact on health inequality in China using Ordered Logit Regression (OLR) and Multi-scale Geographically Weighted Regression (MGWR) model. The results indicate that PM2.5 pollution exacerbate the intergenerational health inequality, and its impacts show inconsistency across family income levels, parental health insurance status, and area of residence. Specifically, it is more difficult for offspring in low-income families to escape from the influence of unhealthy family to become upwardly mobile. Additionally, this health inequality is more significant in households in which at least one parent does not have health insurance. Moreover, the intergenerational solidification caused by PM2.5 pollution is higher in the east and lower in the west. Both the PM2.5 level and solidification effect are high in Beijing-Tianjin-Hebei region, Yangtze River Delta region and central areas of China, which is the focus of air pollution management. These findings suggest that more emphasis should be placed on family-based health promotion. In areas with high PM2.5 pollution levels, resources, subsidies and air pollution protection should be provided for less healthy families with lower incomes and no health insurance.

Ordered Regression Models: a Tutorial.

Ordinal outcomes are common in the social, behavioral, and health sciences, but there is no commonly accepted approach to analyzing them. Researchers make a number of different seemingly arbitrary recoding decisions implying different levels of measurement and theoretical assumptions. As a result, a wide array of models are used to analyze ordinal outcomes, including the linear regression model, binary response model, ordered models, and count models. In this tutorial, we present a diverse set of ordered models (most of which are under-utilized in applied research) and argue that researchers should approach the analysis of ordinal outcomes in a more systematic fashion by taking into consideration both theoretical and empirical concerns, and prioritizing ordered models given the flexibility they provide. Additionally, we consider the challenges that ordinal independent variables pose for analysts that often go unnoticed in the literature and offer simple ways to decide how to include ordinal independent variables in ordered regression models in ways that are easier to justify on conceptual and empirical grounds. We illustrate several ordered regression models with an empirical example, general self-rated health, and conclude with recommendations for building a sounder approach to ordinal data analysis.

Investigating changes in travel behavior over time in response to the COVID-19 pandemic.

The COVID-19 pandemic has significantly affected travel behavior, including the frequency and mode of travel, with the magnitude and nature of these effects varying over time. This study investigates the nature of these relationships by examining changes in various measures of travel behavior, including weekly driving hours, as well as the frequency of telecommuting, use of ride-sharing services, travel for medical purposes, and use of food delivery services. Self-reported travel data from a representative statewide survey of Michigan residents were used to assess changes in these metrics during the early stages of the pandemic, as well as one year thereafter. Random effects linear regression and ordered logit regression models were estimated and the findings show that various changes in behavior had long-lasting effects, while other behaviors generally reverted back toward pre-pandemic levels. In addition, these changes were found to vary across individuals. For example, significant differences were observed based on socio-demographic characteristics, between urban and rural areas, and amongst individuals with differing views on COVID-19 and related government interventions. In general, the pandemic tended to have less pronounced and sustained effects among younger adults as compared to older age groups. Further, those individuals who were opposed to mandatory COVID-19 vaccines were less likely to change their travel behavior, during both the early and latter stages of the pandemic. Changes were observed consistently across most of the travel metrics of interest. Among these, overall driving hours, travel for medical purposes, and ride-sharing were still lower during the latter stages of the pandemic, while telecommuting and the use of food delivery services reverted nearer to pre-pandemic levels.

Determining the effect of air quality on activities of daily living disability: using tracking survey data from 122 cities in China.

BACKGROUND: Current research on activities of daily living (ADLs) disability has mostly focused on the analysis of demographic characteristics, while research on the microcharacteristics of individuals and the macroenvironment is relatively limited, and these studies solely concern the impact of air quality on individual health. METHODS: This study innovatively investigated the impact of air quality on ADL disability by matching micro data of individuals from the China Health and Retirement Longitudinal Study with data of urban environmental quality from 122 cities. In this study, an ordered panel logit model was adopted for the benchmark test, and the two-stage ordered probit model with IV was used for endogenous treatment. RESULTS: This innovative study investigated the impact of air quality on ADL disability by matching individual micro data from the China Health and Retirement Longitudinal Study with urban environmental quality data for 122 cities. The results showed that air quality significantly increased the probability of ADL disability. The positive and marginal effect of air quality on moderate and mild disability was higher. Generally, the marginal effect of air quality on residents' health was negative. In terms of group heterogeneity, the ADL disability of individuals aged over 60 years, those in the high Gross Domestic Product (GDP) group, females, and those in the nonpilot long-term care insurance group was more affected by air quality, and the interaction between air quality and serious illness showed that the deterioration of air quality exacerbated the ADL disability caused by serious illness; that is, the moderating effect was significant. CONCLUSIONS: According to the equilibrium condition of the individual health production function, the ADL disability caused by a 1% improvement in air quality is equivalent to the ADL disability caused by an 89.9652% reduction in serious illness, indicating that the effect of improved air quality is difficult to replace by any other method. Therefore, good air quality can not only reduce ADL disability directly but also reduce serious illness indirectly, which is equivalent to the reduction of ADL disability. This is called the health impact.

Working intentions of medical students in response to healthcare workplace violence and descending resources reform in China.

BACKGROUND: In order to curb healthcare workplace violence (WPV) and better allocate healthcare resources, China launched the descending resources reform in 2013 and tightened the anti-violence legal environment simultaneously. Medical students are expected to reconsider their working intentions of entering the medical market (inter-market effect) and choosing high- or low-level hospitals (intra-market effect) in response to the evolving WPV. The goal of this study was to explore the link between the perceived WPV incidence and medical students' willingness to practice medicine in the context of China's descending resources reform. METHOD: Medical students were selected with cluster sampling from 8 medical colleges in Zhejiang Province, China, and 1497 valid questionnaires were collected by using a five-point unbalanced scale, to perform cross-sectional empirical research using the ordered logit model (OLM). RESULTS: The perceived WPV incidence negatively correlate with the willingness of medical students to practice medicine but positively correlate with their willingness to practice in low-level hospitals, indicating the existence of inter- and intra-market effects. The anti-violence legal environment has no direct link with working intention but contributes to the perceived decline in the incidence of violence. Descending resources reform has simultaneous opposite effects on medical students, with the coexistence of prudent motives driven by reform costs and optimistic expectations of sharing external benefits. CONCLUSIONS: Safety needs and risk aversion motive play an important role in medical students' career choice when facing severe WPV. Tightening of the anti-violence legal environment and the descending resources reform could drive medical students to low-level hospitals.

Willingness to pay for solid waste management improvement in Hawassa city, Ethiopia.

This study used a contingent valuation method to estimate residents' WTP for improved solid waste management in Hawassa city. The improvement in solid waste management includes the relocation of the current landfill and the switch from open donkey carts to covered tractors with a waste compactor for solid waste transportation. A method of iterative bidding was used to ask residents about their WTP, and ordinal logistic regression was used for data analysis. The result of the study indicated that the estimated average WTP of residents was Ethiopian Birr (ETB) 26.57 ($ 0.62) per month. Besides, the study findings showed that waste minimization practices such as reuse, recycle, waste separation and making compost from waste were uncommon at the household level in Hawassa city. The policy implications of the findings are that the Municipality of Hawassa should consider the residents' willingness for improved solid waste management service and adopt the solid waste management improvement project to prevent further public health risks and environmental impacts.

How has the COVID-19 pandemic affected the use of ride-sourcing services? An empirical evidence-based investigation for the Greater Toronto Area.

The ongoing COVID-19 pandemic has fundamentally changed the nature of day-to-day life in cities worldwide. In the transportation sector, COVID-19 appears to have impacted modal preferences. In particular, people seem to be less willing to use modes where they may encounter strangers (such as public transit) and modes that involve coming into contact with shared surfaces (such as ride-sourcing). Given the transformative impact that ride-sourcing services had on urban mobility before the pandemic, it is crucial to understand the effects of COVID-19 on the use of ride-sourcing moving forward. Using data from a web-based survey, this study combines descriptive analysis with the application of a two-stage ordered logit model framework to investigate the impacts of COVID-19 on the utilization of ride-sourcing services in the Greater Toronto Area, including how often ride-sourcing is used and the earliest stage of the pandemic that a person would consider using ride-sourcing. Generally speaking, the use of ride-sourcing has decreased since the start of the pandemic, however, there are also people who are using ride-sourcing more often than they did before the pandemic. The results indicate that the perception of risk, the tendency to take precautions when leaving home, and socio-economic factors influence the earliest stage of the pandemic where a person would consider using ride-sourcing. Overall, it appears that ride-sourcing usage will gradually increase as restrictions are lifted; however, it is unlikely to return to pre-pandemic levels until COVID-19 is no longer considered a public health threat.

The estimation and interpretation of ordered logit models for assessing the factors connected with the productivity of Holstein-Friesian dairy cows in Egypt.

The incorporation of novel technologies such as artificial intelligence, data mining, and advanced statistical methodologies have received wide responses from researchers. This study was designed to model the factors impacting the actual milk yield of Holstein-Friesian cows using the proportional odds ordered logit model (OLM). A total of 8300 lactation records were collected for cows calved between 2005 and 2019. The actual milk yield, the outcome variable, was categorized into three levels: low (< 4500 kg), medium (4500-7500 kg), and high (> 7500 kg). The studied predictor variables were age at first calving (AFC), lactation order (LO), days open (DO), lactation period (LP), peak milk yield (PMY), and dry period (DP). The proportionality assumption of odds using the logit link function was verified for the current datasets. The goodness-of-fit measures revealed the suitability of the ordered logit models to datasets structure. Results showed that cows with younger ages at first calving produce two times higher milk quantities. Also, longer days open were associated with higher milk yield. The highest amount of milk yield was denoted by higher lactation periods (> 250 days). The peak yield per kg was significantly related to the actual yield (P < 0.05). Moreover, shorter dry periods showed about 1.5 times higher milk yield. The greatest yield was observed in the 2nd and 4th parities, with an odds ratio (OR) equal to 1.75, on average. In conclusion, OLM can be used for analyzing dairy cows' data, denoting fruitful information as compared to the other classical regression models. In addition, the current study showed the possibility and applicability of OLM in understanding and analyzing livestock datasets suited for planning effective breeding programs.

Desire to work from home: Results of an Irish study.

Large levels of working from home (WfH) were induced by social distancing and viral control measures undertaken to mitigate the Covid-19 pandemic. Representing an unpredicted change in the way large amounts of people undertake their day to day work, it is expected that the legacy of this event, in terms of significant alterations to work and commuting patterns will have wide-ranging and long-lasting results. However, how persistent the current trends will be, remains an open question. Therefore, there is a need for a well-represented study of employees' preferences for the post-pandemic future and focus on white-collar workers and their well-established attitudes considering their flexibility in terms of workplace arrangements. This paper presents the results of a survey undertaken in Ireland in the summer of 2021 gauging the desire of office workers to WfH, the format that most appeals to them, the consideration of home relocation based on the ability to WfH, and the factors that may explain such preferences. Results indicate high levels of desire to WfH, either full time or partially, with increased desire to WfH positively correlated to pre-pandemic commute length, and to a perceived increase in work productivity and quality of non-work life as a result of time spent WfH. Additionally, a number of workers state that they may consider home relocation based upon the ability to WfH. These results should be interpreted as the desire to WfH or total addressable market that exists, rather than the likely levels of WfH that will be observed post-Covid.

Working from home and its implications for strategic transport modelling based on the early days of the COVID-19 pandemic.

The COVID-19 pandemic has changed the way we go about our daily lives in ways that are unlikely to return to the pre-COVID-19 levels. A key feature of the COVID-19 era is likely to be a rethink of the way we work and the implications this may have on commuting activity. Working from home (WFH) has been the 'new normal' during the period of lockdown, except for essential services that require commuting. In recognition of the new normal as represented by an increasing amount of WFH, this paper develops a model to identify the incidence of WFH and what impact this could have on the amount of weekly one-way commuting trips by car and public transport. Using Wave 1 of an ongoing data collection effort done at the height of the restrictions in March and April 2020 in Australia, we develop a number of days WFH ordered logit model and link it to a zero-inflated Poisson (ZIP) regression model for the number of weekly one-way commuting trips by car and public transport. Scenario analysis is undertaken to highlight the way in which WFH might change the amount of commuting activity when restrictions are relaxed to enable changing patterns of WFH and commuting. The findings will provide one reference point as we continue to undertake similar analysis at different points through time during the pandemic and after when restrictions are effectively removed.

Ovarian hyperstimulation syndrome: a clinical retrospective study on 565 inpatients.

The aim of this study was to analyze clinical manifestations of 565 ovarian hyperstimulation syndrome (OHSS) inpatients in the largest Obstetrics and Gynecology hospital in China from year 2010 to 2017, to get more understanding of epidemiologic features of this disease, and to provide some insight on the diagnosis, treatment, and preventions of OHSS. It is a clinical retrospective study. In the 565 cases that developed OHSS over an eight-year period between 2010 and 2017 were reviewed, we assessed patients' general characteristics, clinical manifestations, treatment, prognosis, and the relationship between different indicators and the severity of OHSS. Totally 12 kinds of ovulation induction protocols (Protocol 1: CC; Protocol 2: Gn; Protocol 3: hCG; Protocol 4: GnRh-a; Protocol 5: CC & Gn; Protocol 6: CC & hCG; Protocol 7: Gn & hCG; Protocol 8: GnRh-a & Gn; Protocol 9: CC & Gn & hCG; Protocol 10: GnRh-a & CC & Gn; Protocol 11: Letrozole & Gn & hCG; Protocol 12:GnRh-a & Letrozole & Gn) were analyzed and the Odds Ratio (OR) of each protocol were calculated. Five hundred and sixty-five patients were reviewed in our study. In all these patients, the number of hospitalizations, mean age, primary infertility rate, and pregnancy rate did not differ through the last 8 years. From which we may infer that the incidence rate of OHSS may not change over the last 8 years. Older patients tend to develop into more severe stage easily. The pregnancy rate was much lower in mild stage patients, but no difference was found between patients in moderate, severe and critical stage. Oocytes retrieval is strongly associated with severity. PCOS history, irregular menstrual cycle and infertility type do not seem to affect the severity of OHSS. Twelve kinds of ovulation induction protocols were analyzed, OR of different protocols were calculated, what is noteworthy is that patients who used GnRh easily developed more severe OHSS than the patients who received oocytes retrieval. We suggest that we may choose ovulation induction protocols according to the OR table while treating women with high-risk factors.

Resident risk attitude analysis in the decision-making management of waste incineration construction.

Environmental pollutants generated by waste incineration plants, such as heavy metals and dioxin, make surrounding residents very sensitive to the construction of such facilities. This sensitivity and anxiety of residents may induce group events, which further leads to the emergence of social risks. Based on risk perception theory, a total of 320 questionnaires was designed and handed out to residents neighboring to Jiangqiao Waste Incineration Plant in Shanghai, China to detect the factors affecting risk attitude toward such plants. Using ordered logit model, it is found that there are four decisive factors including impact on health, information cognitive, objective characteristics, and the attitude of the neighbors. These factors have different influence on resident risk attitudes, in which the attitude of the neighbors is of most significance, followed by the economic-geography characteristics of residents, the information cognitive has minimal impact.

Slowly coming out of COVID-19 restrictions in Australia: Implications for working from home and commuting trips by car and public transport.

With the onset of COVID-19 restrictions and the slow relaxing of many restrictions, it is imperative that we understand what this means for the performance of the transport network. In going from almost no commuting, except for essential workers, to a slow increase in travel activity with working from home (WFH) continuing to be both popular and preferred, this paper draws on two surveys, one in late March at the height of restrictions and one in late May as restrictions are starting to be partially relaxed, to develop models for WFH and weekly one-way commuting travel by car and public transport. We compare the findings as one way to inform us of the extent to which a sample of Australian residents have responded through changes in WFH and commuting. While it is early days to claim any sense of a new stable pattern of commuting activity, this paper sets the context for ongoing monitoring of adjustments in travel activity and WFH, which can inform changes required in the revision of strategic metropolitan transport models as well as more general perspectives on future transport and land use policy and planning.

Will China's Cooperative Medical System fail again? Insight from farmer satisfaction survey.

This paper studied the sustainability of China's New Rural Cooperative Medical System (NCMS) by evaluating the satisfaction rate of its participants-the farmers. The study related the overall satisfaction of the farmers to their satisfaction with the four different aspects of the program. It also identified which personal and program attributes affect the farmers' satisfaction rate. Survey data of 1278 households from 66 counties in Shandong Province of China were collected in 2011 using a multi-stage stratified cluster-sampling method. To overcome the nepotistic barriers in rural China, field surveys in each township were conducted by university students from the same place. Data were analyzed using multiple regressions and structural equation modeling method. The results showed that 86% of the farmers were either satisfied or very satisfied with the NCMS and 82% indicated their intention to continue participating in the program. Aside from its financial benefits, both the publicity and reimbursement procedure of the program were found to be significant factors in influencing the satisfaction of the farmers. Majority of the participants held positive opinions toward the NCMS, contradicting the negative assessments made by many previous studies. Given the high proportion of farmers willing to continue with the program, it is likely to be sustainable in the near future. Greater publicity and education efforts should be made to make the farmers better informed about the program, and measures should be taken to improve its reimbursement procedure and the setting of the premium level.

Drivers of variation in fuel choice for cooking: From the selected towns of North Shoa, Oromia Regional State, Ethiopia.

This study aimed to examine household fuel choice behaviour and drivers of variation in fuel choice for cooking. It utilizes descriptive statistics, ordered logit model and generalized ordered logit model to analyze the influence of independent variables upon dependent variables. The result shows that, mixed fuels are the dominant sources of energy with 43.75 % followed by unclean fuel with 33.25 % and then clean fuel with 23 %. This confirms 'households' Fuel-Stacking behaviour. The result of the ordered logit model suggest that variables like family size, per monthly income, the gender of household head, household ownership of electric meter, ownership of housing unit, marital status, age, occupation, educational levels of household heads, and the number of the adult females are statistically significant at 1 %, 5 %, and 10 % while, place of residence and occupation (self-non agriculture) are statistically insignificant to determine fuel choice. Identifying the fuels which are chosen by households should serve as a guide for government and policymakers in the formulation and implementation of policies and strategies that will guarantee optimal access to clean energy sources. Therefore, the government should improve the supply and distribution of electric meters by subsidizing them.

Factors associated with financial risk due to health spending in Argentina.

This article aims to assess the association between household demographic and socioeconomic characteristics and catastrophic health expenditure (CHE) in Argentina during 2017-2018. CHE was estimated as the proportion of household consumption capacity (using both income and total consumption in separate estimations) allocated for Out-of-Pocket (OOP) health expenditure. For assessing the determinants, we estimated a generalized ordered logit model using different intensities of CHE (10%, 15%, 20% and 25%) as the ordinal dependent variable, and socioeconomic, demographic and geographical variables as explanatory factors. We found that having members older than 65 years and with long-term difficulties increased the likelihood of incurring CHE. Additionally, having an economically inactive household head was identified as a factor that increases this probability. However, the research did not yield consistent results regarding the relationship between public and private health insurance and consumption capacity. Our results, along with the robustness checks, suggest that the magnitude of the coefficients for the household head characteristics could be exaggerated in studies that overlook the attributes of other household members. In addition, these results emphasize the significance of accounting for long-term difficulties and indicate that omitting this factor could overestimate the impact of members aged over 65.

Analysis of pedestrian-two-wheeler conflicts at green light digital countdown signals: A random parameter ordered logit model approach.

The rising prevalence of e-bikes and shared bikes in transportation modes adds complexity to pedestrian movement at intersections. The conflict technique is a substitute for collisions in analyzing pedestrian safety at digital countdown signal intersections. Pedestrian and two-wheeler trajectories were obtained using Unmanned Aerial Vehicle (UAV) and T-Analyst software. The severity of pedestrian-two-vehicle conflicts was assessed using indicators such as Time to Collision (TTC), Post Encroachment Time (PET), and Yaw Rate Ratio (YRR), along with the fuzzy C-mean clustering method. An analysis of the impact of pedestrian characteristics, cyclist characteristics, and road conflict factors on severity was conducted using a random parameter ordered logit model. A total of 630 valid conflicts were identified, comprising 105 potential conflicts, 242 minor conflicts, and 283 serious conflicts. More minor and serious conflicts occurred in Signal 1 and Signal 2. Serious conflicts mainly occurred in road Zone 2, Zone 3, and Zone 5, while minor conflicts were more frequent in Zone 4 and Zone 5. Pedestrian crossing at Signal 2 increased the conflict severity, and the refuge island had a similar effect. Cyclists passing the conflict point first reduced the probability of serious conflicts. Older adults are safer at countdown signal intersections than young people. It is essential to enhance the awareness of digital countdown signals among youth. Managers should consider diverting two-wheelers during peak hours and encourage cyclists to walk through crosswalks.

Evaluating the traffic safety performance of left-turn waiting areas at signalized intersections.

Left-turn waiting area (LWA) is an innovative traffic design that is popularly applied to improve the traffic capacity of signalized intersections in China. The traffic safety impacts of the LWA, however, have not been fully discussed in previous studies. Thus, the study aims to evaluate the safety performance of the LWA by means of the traffic conflict technique. A field investigation was conducted to collect the post-encroachment time (PET) of conflicts and relevant variables at the signalized intersections in Jinhua, China. The Chi-square and two sample t-tests were adopted to examine the difference in conflict distribution between the intersections with and without LWA. The random parameter ordered logit model was employed to identify the factors contributing to the risks of vehicular collisions. Results indicate that (1) intersections with LWA are generally associated with more merging conflicts; (2) there are no significant discrepancies in the PET values between intersections with and without LWA; and (3) factors such as the number of left-turn lanes, number of receiving lanes, conflict type, vehicle type, driving direction, stopping outside LWA and overtaking behavior are identified to significantly impact the traffic conflicts. The findings serve to develop the countermeasures to ensure the safe operation of LWA.

Is there a LINKAGE between credit access, land use, and crop diversification in achieving food security? Evidence from cocoa-producing households in Nigeria.

Cocoa farmers in Nigeria adopt crop diversification to safeguard the food security of their households. Although credit and land are thought to play a vital role in crop diversification, they continue to have limited access to credit and land. This study investigated the linkages between access to credit, land use, crop diversification, and food security with a focus on cocoa farming households. A multistage sampling procedure was used to obtain data for the study. Data were analyzed with the aid of descriptive statistics, the Heifindahl index, the Tobit regression model, the food consumption score, and the ordered Logit regression model. The results for the entire respondents showed mean values of 55 years for age, 31 years for farming experience, 6 people for household size, and 5 ha for farm size. Heifindahl index shows 38.67 % of the respondents had low crop diversification in the study area. Tobit regression model reveals that access to credit, farming experience, cooperative organization, access to extension service, farm size, distance to farms, and labour are the main albeit significant factors that determine crop diversification among cocoa farming households. Food consumption score revealed that 46.67 % were poor, 30.67 % were at the borderline and about 27.67 % were within the acceptable threshold. The ordered logit model revealed that crop diversification index, formal education, access to credit, farm size, land use, and farming experience have a significant influence on the food security of households. The study concluded that there is a positive relationship between access to credit, land use, crop diversification, and food security. Therefore, the government and financial institutions should make credit facilities accessible to cocoa farmers to improve their livelihood.

Investigating effective factors on rural crash severity at marginal areas around cities in Iran: a partial proportional odds modelling approach.

Over the past decade, rural crashes have been responsible for an average of 65% of crash-induced casualties in Iran. Evidence from prior studies reveals that a significant number of these rural crashes occur at marginal areas around cities. Thus, Exclusive crash severity models should be developed to identify the factors associated with higher injury and fatality probabilities in these areas. In this study, a partial proportional odds (PPO) model was formulated using the rural crash data collected from roads leading to the city of Isfahan. The PPO model holds the ordinal nature of crash observations and allows for different influences of independent variables on various crash severity levels. Insights derived from the results reveal that factors such as vehicle traffic maintaining an average speed exceeding 95 km/h, the occurrence of multi-vehicle crashes, the incidence of overturn-type crashes, the at-fault vehicle being a truck/trailer and at-fault or not-at-fault vehicle being a motorcycle, increase the likelihood of more severe rural crashes. Conversely, a foreign vehicle being at-fault, and the driver of the at-fault vehicle aged between 30 and 40 years, tend to diminish the occurrence of severe crashes at marginal areas around cities.