scholarly journals Intersectional and Entangled Risks: An Empirical Analysis of Disasters and Landfills

2021 ◽  
Vol 3 ◽  
Author(s):  
Clare E. B. Cannon
Keyword(s):  
Environmental Justice ◽  
Women Of Color ◽  
Negative Binomial ◽  
Global Climate ◽  
Negative Binomial Regression ◽  
Hazardous Waste Sites ◽  
Climate Risks ◽  
Intersectionality Theory ◽  
Binomial Regression ◽  
And Gender

Landfills are environmental hazards linked to harms, such as the production of greenhouse gases and the accumulation of toxins in natural and human systems. Although environmental justice research has established such unwanted land uses as hazardous waste sites occur in poor communities and communities of color, less is known about the relationship between landfills and gender. As a driver of global climate change, there is also limited research into the relationships among disasters, landfills, and climate-related risks. To fill this gap, the current study uses an intersectional approach to theorize and empirically analyze relationships among landfills, disasters, race, class, and gender. We employ negative binomial regression to analyze a unique U.S. dataset of landfill counts, total number of disasters, and socio-demographic characteristics, including the use of two-way interactions among race, sex, and socioeconomic status variables, and number of federally-declared disasters that influence landfill counts. Findings suggest that intersecting axes of social location (specifically gender and race) are not multiplicative when it comes to landfills or the environmental risks they pose, but we argue may be entangled—that is related in non-linear and complicated ways. Using intersectionality theory, we interpret the findings to indicate that women of color are agents of resistance enacting their own forms of power against dominant structural arrangements that produce and maintain environmental injustices. Conclusions and implications for environmental justice, intersectionality, and climate risks are further discussed.

Mandated Representation: Exploring the Consequences of Gender Quota Design on Parliamentary Activity

2020 ◽  
Author(s):  
Eva-Maria Euchner ◽  
Elena Frech
Keyword(s):  
Negative Binomial ◽  
Gender Diversity ◽  
Negative Binomial Regression ◽  
Gender Quotas ◽  
Binomial Regression ◽  
Interdisciplinary Framework ◽  
Research Gap ◽  
And Gender ◽  
Gender Quota ◽  
The Impact

Abstract Although the scholarship on legislative behaviour widely agrees that electoral rules determine parliamentary activities, surprisingly little is known on the impact of gender quotas. We contribute to this research gap by developing an innovative interdisciplinary framework and by exploring it based on a unique dataset on varying gender quota designs throughout EU countries and parties running for the 7th term of the European Parliament (2009–2014). Based on the scholarship on gender diversity in management teams and the research on gendered processes in political parties, we argue that especially mandated gender quotas stimulate processes of social categorisation, intergroup biasing and competition due to a normative mis-fit between conceptions of gender equality and gender quotas, which in turn influences coordination and communication and hence, parliamentary activity more generally. Combining negative-binomial regression models and expert interviews, we indeed find that mandated gender quotas promote ‘individual’ parliamentary activities (e.g. speeches) and tend to impede ‘collaborative’ parliamentary activities (e.g. reports).

scholarly journals Expressway Traffic Accidents Involving Human Injuries and Fatalities in Ethiopia: Negative Binomial Regression Model

2021 ◽  
Author(s):  
Yesuf Abdela Mustefa ◽  
Addis Belayhun
Keyword(s):  
Traffic Accidents ◽  
Negative Binomial ◽  
Weather Condition ◽  
Negative Binomial Regression ◽  
Weather Conditions ◽  
Negative Binomial Regression Model ◽  
Level Of Education ◽  
Binomial Regression ◽  
Windy Weather ◽  
And Gender

Abstract Objective The purpose of this study is to provide insights and to model significant determinants of accidents involving injuries and fatalities using Ethiopian Toll Roads Enterprise data. Besides, we utilized recent dataset recorded from September, 2014 to December, 2019. We applied the most appropriate but forwent statistical model. Moreover, we examined the significance of the effects of drivers’ age and gender that have not been the cases in the literatures. Results We found that the number of injuries in accidents were significantly determined by type of vehicles, ownership status of vehicles, accident time weather condition, driver-vehicle relationship, drivers’ level of education, and drivers’ age. Heavy trucks were more likely to cause more number of injuries than medium or small vehicles. Hot and windy weather conditions were associated with higher probability of the number of injuries. The likelihood of the number of injuries were lower when drivers are owner of the vehicle; drivers level of education is above secondary school; and the age of the driver is between 18 and 23 years old. Moreover, due concern needs to be given for traffic road rules.

scholarly journals A Statistical Analysis of Weight Gain During the Freshman Year of College

2015 ◽  
Vol 4 (1) ◽  
pp. 144-151
Author(s):  
Elaine Perrin ◽  
Travis Sellers ◽  
Lorena Hernandez Maxwell ◽  
Malachi Morgan ◽  
Sherod-Malik Davis ◽  
...  
Keyword(s):  
Weight Gain ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Contributing Factors ◽  
Freshman Year ◽  
Binomial Regression ◽  
Societal Changes ◽  
And Gender ◽  
Objective Being ◽  
Question Survey

This study examined freshman weight gain and its contributing factors, with the objective being to determine what environmental and societal changes in the college freshman experience associate with weight gain. We designed a 27-question survey which asked participants about their lifestyles during their freshman year in college.  Responses were obtained through social media from 95 student participants across 37 United States colleges and universities.  The resulting data distribution of weight gained among surveyed freshmen was right-skewed with a median weight gain of zero and an interquartile range of 6.5 lbs.  In particular, 52% of the survey respondents reported no weight gain. Accordingly, we modeled the data via a zero-inflated negative binomial regression analysis to investigate what student characteristics prior to and during his/her freshman year are associated with weight gain and likewise determine an estimated probability of no weight gain in the freshman year.  Our study and statistical model found significant associations between freshman weight gain and the choice of major, average amount of nightly sleep, one’s relationship with his/her parents, and gender.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Association between fatality rate of COVID-19 and selenium deficiency in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hai-Yang Zhang ◽  
An-Ran Zhang ◽  
Qing-Bin Lu ◽  
Xiao-Ai Zhang ◽  
Zhi-Jie Zhang ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Viral Infections ◽  
Case Fatality ◽  
Selenium Deficiency ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Fatality Rate ◽  
Selenium Content ◽  
Individual Level ◽  
Binomial Regression

Abstract Background COVID-19 has impacted populations around the world, with the fatality rate varying dramatically across countries. Selenium, as one of the important micronutrients implicated in viral infections, was suggested to play roles. Methods An ecological study was performed to assess the association between the COVID-19 related fatality and the selenium content both from crops and topsoil, in China. Results Totally, 14,045 COVID-19 cases were reported from 147 cities during 8 December 2019–13 December 2020 were included. Based on selenium content in crops, the case fatality rates (CFRs) gradually increased from 1.17% in non-selenium-deficient areas, to 1.28% in moderate-selenium-deficient areas, and further to 3.16% in severe-selenium-deficient areas (P = 0.002). Based on selenium content in topsoil, the CFRs gradually increased from 0.76% in non-selenium-deficient areas, to 1.70% in moderate-selenium-deficient areas, and further to 1.85% in severe-selenium-deficient areas (P < 0.001). The zero-inflated negative binomial regression model showed a significantly higher fatality risk in cities with severe-selenium-deficient selenium content in crops than non-selenium-deficient cities, with incidence rate ratio (IRR) of 3.88 (95% CIs: 1.21–12.52), which was further confirmed by regression fitting the association between CFR of COVID-19 and selenium content in topsoil, with the IRR of 2.38 (95% CIs: 1.14–4.98) for moderate-selenium-deficient cities and 3.06 (1.49–6.27) for severe-selenium-deficient cities. Conclusions Regional selenium deficiency might be related to an increased CFR of COVID-19. Future studies are needed to explore the associations between selenium status and disease outcome at individual-level.

scholarly journals Statistical models for analyzing count data: predictors of length of stay among HIV patients in Portugal using a multilevel model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ahmed Nabil Shaaban ◽  
Bárbara Peleteiro ◽  
Maria Rosario O. Martins
Keyword(s):  
Length Of Stay ◽  
Regression Model ◽  
Random Effects ◽  
Count Data ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Comprehensive Approach ◽  
Negative Binomial Regression Model ◽  
Hiv Patients ◽  
Binomial Regression

Abstract Background This study offers a comprehensive approach to precisely analyze the complexly distributed length of stay among HIV admissions in Portugal. Objective To provide an illustration of statistical techniques for analysing count data using longitudinal predictors of length of stay among HIV hospitalizations in Portugal. Method Registered discharges in the Portuguese National Health Service (NHS) facilities Between January 2009 and December 2017, a total of 26,505 classified under Major Diagnostic Category (MDC) created for patients with HIV infection, with HIV/AIDS as a main or secondary cause of admission, were used to predict length of stay among HIV hospitalizations in Portugal. Several strategies were applied to select the best count fit model that includes the Poisson regression model, zero-inflated Poisson, the negative binomial regression model, and zero-inflated negative binomial regression model. A random hospital effects term has been incorporated into the negative binomial model to examine the dependence between observations within the same hospital. A multivariable analysis has been performed to assess the effect of covariates on length of stay. Results The median length of stay in our study was 11 days (interquartile range: 6–22). Statistical comparisons among the count models revealed that the random-effects negative binomial models provided the best fit with observed data. Admissions among males or admissions associated with TB infection, pneumocystis, cytomegalovirus, candidiasis, toxoplasmosis, or mycobacterium disease exhibit a highly significant increase in length of stay. Perfect trends were observed in which a higher number of diagnoses or procedures lead to significantly higher length of stay. The random-effects term included in our model and refers to unexplained factors specific to each hospital revealed obvious differences in quality among the hospitals included in our study. Conclusions This study provides a comprehensive approach to address unique problems associated with the prediction of length of stay among HIV patients in Portugal.

scholarly journals Association between breakfast skipping and metabolic outcomes by sex, age, and work status stratification

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jun Heo ◽  
Won-Jun Choi ◽  
Seunghon Ham ◽  
Seong-Kyu Kang ◽  
Wanhyung Lee
Keyword(s):  
Regression Analysis ◽  
Negative Binomial ◽  
Metabolic Diseases ◽  
Young Male ◽  
Negative Binomial Regression ◽  
Final Analysis ◽  
Work Status ◽  
Breakfast Skipping ◽  
Metabolic Outcomes ◽  
Binomial Regression

Abstract Background The association between breakfast skipping and abnormal metabolic outcomes remains controversial. A comprehensive study with various stratified data is required. Objective The aim of this study was to investigate the relationship between abnormal metabolic outcomes and breakfast skipping by sex, age, and work status stratification. Methods We used data from the Korea National Health and Nutrition Examination Surveys from 2013 to 2018. A total of 21,193 (9022 men and 12,171 women) participants were included in the final analysis. The risk of metabolic outcomes linked to breakfast skipping was estimated using the negative binomial regression analysis by sex, work status, and age stratification. Results A total of 11,952 (56.4%) participants consumed breakfast regularly. The prevalence of abnormal metabolic outcomes was higher among those with irregular breakfast consumption habits. Among young male workers, negative binomial regression analysis showed that irregular breakfast eaters had a higher risk of abnormal metabolic outcomes, after adjusting for covariates (odds ratio, 1.15; 95% confidence interval, 1.03–1.27). Conclusions The risk of abnormal metabolic outcomes was significant in young men in the working population. Further studies are required to understand the association of specific working conditions (working hours or shift work) with breakfast intake status and the risk of metabolic diseases.

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