scholarly journals Faecal contamination pathways of shallow groundwater in low-income urban areas: implications for water resource planning and management

2021 ◽  
Author(s):  
Jacintha Gumoteyo Nayebare ◽  
Michael M. Owor ◽  
Robinah Kulabako ◽  
Richard Graham Taylor
Keyword(s):  
Linear Regression ◽  
Low Income ◽  
Urban Areas ◽  
Shallow Groundwater ◽  
Multiple Linear Regression Model ◽  
Resource Planning ◽  
Water Sources ◽  
Linear Regression Models ◽  
Faecal Contamination ◽  
E Coli

Abstract Shallow groundwater is vulnerable to faecal contamination, especially in low-income urban areas where use of on-site sanitation facilities is high. This paper explores statistical relationships between potential factors influencing contaminant pathways (i.e., variables) and observed faecal contamination of shallow groundwater, represented by nitrate concentrations and counts of Escherichia coli (i.e., response function) in a small, growing town in Uganda over dry and wet seasons in 2018 and 2019. A statistically significant (p = 0.004) multiple linear regression model from dry-season E. coli counts in 2018 identifies medium sanitary risk levels and modes of construction as significant pathways (p = 0.01). Water source depth (<20 m) and proximity (>10 m) to a pit latrine were also significant (p<0.05) in both hydrogeological formations. No significant linear regression models were established for NO3 during both seasons due to low pH and rapid infiltration velocities; inconsistent sample timing during the wet season impaired the significance of the statistical models of E. coli counts. We show that modes of construction of water sources and pit latrines play key roles in determining the quality of the shallow groundwater in urban environments. Greater emphasis is therefore required to improve the functionality and sustainability of on-site water sources and pit latrines.

Folate Nutritional Status among Psoriasis Patients not Exposed to Antifolate Drug

2020 ◽  
Vol 16 (4) ◽  
pp. 543-553
Author(s):  
Luciana Y. Tomita ◽  
Andréia C. da Costa ◽  
Solange Andreoni ◽  
Luiza K.M. Oyafuso ◽  
Vânia D’Almeida ◽  
...  
Keyword(s):  
Folic Acid ◽  
Linear Regression ◽  
Multiple Linear Regression Model ◽  
Folate Intake ◽  
Serum Folate ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Folic Acid Fortification ◽  
Plasma Folate ◽  
Psoriasis Severity

Background: Folic acid fortification program has been established to prevent tube defects. However, concern has been raised among patients using anti-folate drug, i.e. psoriatic patients, a common, chronic, autoimmune inflammatory skin disease associated with obesity and smoking. Objective: To investigate dietary and circulating folate, vitamin B12 (B12) and homocysteine (hcy) in psoriatic subjects exposed to the national mandatory folic acid fortification program. Methods: Cross-sectional study using the Food Frequency Questionnaire, plasma folate, B12, hcy and psoriasis severity using the Psoriasis Area and Severity Index score. Median, interquartile ranges (IQRs) and linear regression models were conducted to investigate factors associated with plasma folate, B12 and hcy. Results: 82 (73%) mild psoriasis, 18 (16%) moderate and 12 (11%) severe psoriasis. 58% female, 61% non-white, 31% former smokers, and 20% current smokers. Median (IQRs) were 51 (40, 60) years. Only 32% reached the Estimated Average Requirement of folate intake. Folate and B12 deficiencies were observed in 9% and 6% of the blood sample respectively, but hyperhomocysteinaemia in 21%. Severity of psoriasis was negatively correlated with folate and B12 concentrations. In a multiple linear regression model, folate intake contributed positively to 14% of serum folate, and negative predictors were psoriasis severity, smoking habits and saturated fatty acid explaining 29% of circulating folate. Conclusion: Only one third reached dietary intake of folate, but deficiencies of folate and B12 were low. Psoriasis severity was negatively correlated with circulating folate and B12. Stopping smoking and a folate rich diet may be important targets for managing psoriasis.

scholarly journals Impact of Age-Related Vision Changes on Driving

2020 ◽  
Vol 17 (20) ◽  
pp. 7416
Author(s):  
Sonia Ortiz-Peregrina ◽  
Carolina Ortiz ◽  
Miriam Casares-López ◽  
José J. Castro-Torres ◽  
Luis Jiménez del Barco ◽  
...  
Keyword(s):  
Linear Regression ◽  
Visual Function ◽  
Driving Simulator ◽  
Multiple Linear Regression Model ◽  
Driving Performance ◽  
Older Drivers ◽  
Linear Regression Models ◽  
Simulated Driving ◽  
Age Related ◽  
Intraocular Straylight

Aging leads to impaired visual function, which can affect driving—a very visually demanding task—and has a direct impact on an individual’s quality of life if their license is withdrawn. This study examined the associations between age-related vision changes and simulated driving performance. To this end, we attempted to determine the most significant visual parameters in terms of evaluating elderly drivers’ eyesight. Twenty-one younger drivers (aged 25–40) were compared to 21 older drivers (aged 56–71). Study participants were assessed for visual acuity, contrast sensitivity, halos, and intraocular straylight, which causes veiling luminance on the retina and degrades vision. Driving performance was evaluated using a driving simulator. The relationships between simulated driving performance and the visual parameters tested were examined with correlation analyses and linear regression models. Older drivers presented impairment in most visual parameters (p < 0.05), with straylight being the most significantly affected (we also measured the associated effect size). Older drivers performed significantly worse (p < 0.05) in the simulator test, with a markedly lower performance in lane stability. The results of the multiple linear regression model evidenced that intraocular straylight is the best visual parameter for predicting simulated driving performance (R2 = 0.513). Older drivers have shown significantly poorer results in several aspects of visual function, as well as difficulties in driving simulator performance. Our results suggest that the non-standardized straylight evaluation could be significant in driver assessments, especially at the onset of age-related vision changes.

scholarly journals Psychiatric Disorders and Alcohol Consumption Among Low-Income African Americans:Gender Differences

2019 ◽  
Vol 9 (4) ◽  
pp. 86 ◽  
Author(s):  
Sharon Cobb ◽  
Shervin Assari
Keyword(s):  
Alcohol Consumption ◽  
Alcohol Use ◽  
Linear Regression ◽  
Low Income ◽  
Regression Models ◽  
Future Research ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Men And Women ◽  
Compulsive Disorder

Background: Although cooccurrence of nonsubstance use disorders (non-SUDs) and substance use is well-established in the literature, most of what we know in this regard is derived from studies that have recruited predominantly White sample populations. As a result, there is a gap in knowledge on this link among low-income African Americans (AAs). There is also a need to understand how low-income AA men and women differ in these associations. Objective: To study whether there is an association between number of non-SUDs and amount of alcohol consumption by AA adults, and whether this association varies between AA men and women. Methods: This cross-sectional study recruited a nonrandom sample of 150 AA adults with non-SUDs (i.e., major depression, bipolar disorders, obsessive–compulsive disorder, paranoid disorder, panic disorder, posttraumatic stress disorder (PTSD), and schizoaffective disorder). The independent variable was the number of non-SUDs. The dependent variable was the amount of alcohol consumption. Age, socioeconomic status (educational attainment and household income), and self-rated health were covariates. Gender was the moderator. Linear regression models were used to analyze the data. Results: A higher number of non-SUDs was not associated with a higher amount of alcohol use in the pooled sample of AA adults. We, however, found a significant interaction between gender and number of non-SUDs on the amount of alcohol use, suggesting a stronger effect of non-SUDs on alcohol consumption in AA men than in AA women. Gender-stratified linear regression models showed a positive association between number of non-SUDs and amount of alcohol consumption in AA men but not in AA women. Conclusion: Non-SUDs impact alcohol use of AA men but not women. Future research should test whether AA men may have a higher tendency to turn to alcohol to regulate their emotions and cope with psychological pain due to multiple non-SUDs. The results also suggest that integration of services for SUDs and non-SUDs may be more relevant to provision of mental health services for AA men than AA women.

scholarly journals Pedestrian crossing model in urban street (Case study on commercial area in Bandung)

2018 ◽  
Vol 181 ◽  
pp. 02004
Author(s):  
Sony Sulaksono Wibowo ◽  
Rian Wicaksana
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Group Size ◽  
Multiple Linear Regression Model ◽  
Delay Model ◽  
Affecting Factors ◽  
Linear Regression Models ◽  
Urban Street ◽  
Commercial Area ◽  
Pedestrian Crossing

Pedestrians who cross without any crossing facilities and under mixed-traffic tend to have varying responses. The responses can be analyzed by using multiple linear regression model, with pedestrian crossing delay and pedestrian crossing speed set as response variables. This research aims to develop two pedestrian crossing models based on the condition at the midblock part of urban street, in particular commercial area and without specific crossing facilities. The two models are pedestrian crossing delay model and pedestrian crossing speed model. The affecting factors are considered in linear relationship and the multiple-linear regression models are used. The principal factor in the pedestrian crossing delay model is group size of more than 3 persons, while in the model of pedestrian crossing speed, the principal factors are number of group size and pedestrian baggage. The mean of pedestrian crossing delay was about 3 seconds while pedestrian crossing speed was about 1 m/s.

scholarly journals Multiple Linear Regression Model of Meningococcal Disease in Ukraine: 1992–2015

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Hennadii Mokhort
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Meningococcal Disease ◽  
Total Population ◽  
Linear Models ◽  
National Level ◽  
Multiple Linear Regression Model ◽  
National Database ◽  
Linear Regression Models ◽  
Susceptible Population

Estimating the rates of invasive meningococcal disease (IMD) from epidemiologic data remains critical for making public health decisions. In Ukraine, such estimations have not been performed. We used epidemiological data to develop a national database. These data were used to estimate the population susceptible to IMD and identify the prevalence of asymptomatic carriers of N. meningitidis using simple epidemiological models of meningococcal disease that may be used by the national policy makers. The goal was to create simple, easily understood analysis of patterns of the infection within Ukraine that would capture the major features of the infection dynamics. Studies used nationally reported data during 1992–2015. A logic model identified the prevalence of carriage and the proportion of the population susceptible to IMD as key drivers of IMD incidence. Multiple linear regression models for all ages (total population) and for children ≤14 years old were fit to national-level data. Linear models with the incidence of IMD as an outcome were highly associated with carriage and estimated susceptible population in both total population and children (R2 = 0.994 and R2 = 0.978, respectively). The susceptibility rate to IMD in the study total population averaged 0.0034 ± 0.0009% annually. At the national level, IMD can be characterized by the simple interaction between the prevalence of asymptomatic carriage and the proportion of the susceptible population. IMD association with prevalence rates of carriage and the proportion of susceptible population is sufficiently strong for national-level planning of intervention strategies for IMD.

scholarly journals Factors associated with parasite dominance in fishes from Brazil

2016 ◽  
Vol 25 (2) ◽  
pp. 225-230
Author(s):  
Cristina Fernandes do Amarante ◽  
Wagner de Souza Tassinari ◽  
Jose Luis Luque ◽  
Maria Julia Salim Pereira
Keyword(s):  
Linear Regression ◽  
Body Length ◽  
Regression Models ◽  
Mixed Model ◽  
Multiple Linear Regression Model ◽  
Mixed Effects ◽  
The Body ◽  
Linear Regression Models ◽  
Biological Aspects ◽  
The Relationship

Abstract The present study used regression models to evaluate the existence of factors that may influence the numerical parasite dominance with an epidemiological approximation. A database including 3,746 fish specimens and their respective parasites were used to evaluate the relationship between parasite dominance and biotic characteristics inherent to the studied hosts and the parasite taxa. Multivariate, classical, and mixed effects linear regression models were fitted. The calculations were performed using R software (95% CI). In the fitting of the classical multiple linear regression model, freshwater and planktivorous fish species and body length, as well as the species of the taxa Trematoda, Monogenea, and Hirudinea, were associated with parasite dominance. However, the fitting of the mixed effects model showed that the body length of the host and the species of the taxa Nematoda, Trematoda, Monogenea, Hirudinea, and Crustacea were significantly associated with parasite dominance. Studies that consider specific biological aspects of the hosts and parasites should expand the knowledge regarding factors that influence the numerical dominance of fish in Brazil. The use of a mixed model shows, once again, the importance of the appropriate use of a model correlated with the characteristics of the data to obtain consistent results.

scholarly journals Um modelo alternativo de risco para companhias não-financeiras aplicado ao setor brasileiro de papel e celulose

2009 ◽  
Vol 7 (3) ◽  
pp. 347
Author(s):  
Hsia Hua Sheng ◽  
Cristiane Karcher ◽  
Paulo Hubert Jr.
Keyword(s):  
At Risk ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Financial Risk ◽  
Risk Measure ◽  
Multiple Linear Regression Model ◽  
Principal Component ◽  
Linear Regression Models ◽  
Explanatory Factors ◽  
Paper And Pulp

Earnings at Risk (EaR) is a financial risk measure that can be applied to non-financial companies, similarly to Cash Flow at Risk (CFaR). It is based on a relation that can be quantified using a multiple linear regression model, where the dependent variable is the change on the company's results and the independent variables are changes in distinct risk factors. The presence of correlation between explanatory factors (multicollinearity) in this kind of model may cause problems when calculating EaR and CFaR. In this paper, we indicate some possible consequences of these problems when calculating EaR, and propose a method to solve it based on Principal Component Analysis technique. To test the model, we choose the Brazilian agriculture-business industry, more specifically the paper and pulp sectors. We will show that, on the absence of significant correlation between variables, the proposed model has equivalent performance to usual multiple linear regression models. We find evidence that when correlation appears, the model here proposed yields more accurate and reliable forecasts.

scholarly journals WASH conditions in a small town in Uganda: how safe are on-site facilities?

2019 ◽  
Vol 10 (1) ◽  
pp. 96-110 ◽  
Author(s):  
J. G. Nayebare ◽  
M. M. Owor ◽  
R. Kulabako ◽  
L. C. Campos ◽  
E. Fottrell ◽  
...  
Keyword(s):  
Water Supply ◽  
Low Income ◽  
Water Sources ◽  
Low Income Countries ◽  
Household Surveys ◽  
Point Mapping ◽  
Faecal Contamination ◽  
Site Water ◽  
Joint Monitoring ◽  
Water Supply And Sanitation

Abstract Inadequate hygiene coupled with the conjunctive use of the shallow subsurface as both a source of water and repository of faecal matter pose substantial risks to human health in low-income countries undergoing rapid urbanisation. To evaluate water, sanitation and hygiene (WASH) conditions in a small, rapidly growing town in central Uganda (Lukaya) served primarily by on-site water supply and sanitation facilities, water-point mapping, focus group discussions, sanitary-risk inspections and 386 household surveys were conducted. Household surveys indicate high awareness (82%) of domestic hygiene (e.g. handwashing, boiling water) but limited evidence of practice. WHO Sanitary Risk Surveys and Rapid Participatory Sanitation System Risk Assessments reveal further that community hygiene around water points and sanitation facilities including their maintenance is commonly inadequate. Spot sampling of groundwater quality shows widespread faecal contamination indicated by enumerated thermo-tolerant coliforms (TTCs) (Escherichia coli) ranging from 0 to 104 cfc/100 mL and nitrate concentrations that occasionally exceed 250 mg/L. As defined by the WHO/UNICEF Joint Monitoring programme, there are no safely managed water sources in Lukaya; ∼55% of improved water sources comprising primarily shallow hand-dug wells show gross faecal contamination by E. coli; and 51% of on-site sanitation facilities are unimproved. Despite the critical importance of on-site water supply and sanitation facilities in low-income countries to the realisation of UN Sustainable Goal 6 (access to safe water and sanitation for all by 2030), the analysis highlights the fragility and vulnerability of these systems where current monitoring and maintenance of communal facilities are commonly inadequate.

scholarly journals Inequalities in microbial contamination of drinking water supplies in urban areas: the case of Lilongwe, Malawi

2016 ◽  
Vol 14 (5) ◽  
pp. 851-863 ◽  
Author(s):  
Akosua Sarpong Boakye-Ansah ◽  
Giuliana Ferrero ◽  
Maria Rusca ◽  
Pieter van der Zaag
Keyword(s):  
Escherichia Coli ◽  
Water Quality ◽  
Drinking Water ◽  
Water Supply ◽  
Low Income ◽  
Urban Areas ◽  
Microbial Contamination ◽  
Water Storage ◽  
Faecal Contamination ◽  
Household Level

Over past decades strategies for improving access to drinking water in cities of the Global South have mainly focused on increasing coverage, while water quality has often been overlooked. This paper focuses on drinking water quality in the centralized water supply network of Lilongwe, the capital of Malawi. It shows how microbial contamination of drinking water is unequally distributed to consumers in low-income (unplanned areas) and higher-income neighbourhoods (planned areas). Microbial contamination and residual disinfectant concentration were measured in 170 water samples collected from in-house taps in high-income areas and from kiosks and water storage facilities in low-income areas between November 2014 and January 2015. Faecal contamination (Escherichia coli) was detected in 10% of the 40 samples collected from planned areas, in 59% of the 64 samples collected from kiosks in the unplanned areas and in 75% of the 32 samples of water stored at household level. Differences in water quality in planned and unplanned areas were found to be statistically significant at p &lt; 0.05. Finally, the paper shows how the inequalities in microbial contamination of drinking water are produced by decisions both on the development of the water supply infrastructure and on how this is operated and maintained.

scholarly journals Estimating the Spatial Distribution of Soil Organic Carbon and Soil Total Nitrogen Stocks by Remote Sensing Methods: A Case Study in a Forest-dominated Alpine Watershed, Western China

2021 ◽  
Author(s):  
chao wang ◽  
Chuanyan Zhao ◽  
Kaiming Li ◽  
Shouzhang Peng ◽  
Ying Wang
Keyword(s):  
Remote Sensing ◽  
Linear Regression ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Total Nitrogen ◽  
Vegetation Index ◽  
Multiple Linear Regression Model ◽  
Western China ◽  
Linear Regression Models ◽  
Soil Total Nitrogen

Abstract Soil organic carbon and soil total nitrogen stocks are important indicators for evaluating soil health and stability. Accurately predicting the spatial distribution of soil organic carbon and total nitrogen stocks is an important basis for mitigating global warming, ensuring regional food security, and maintaining the sustainable development of ecologically fragile areas. On the basis of field sampling data and remote sensing technology, this study divided the topsoil (0–30 cm) into three soil layers of 0–10 cm, 10–20 cm, and 20–30 cm to carry out soil organic carbon and soil total nitrogen stocks estimation experiments in the Qilian Mountains in western China. A multiple linear regression model and a stepwise multiple linear regression model were used to estimate soil organic carbon and soil total nitrogen stocks. A total of 119 topsoil samples and nine remotely sensed environmental variables were collected and used for model development and validation. The results indicated that these two linear regression models showed good performance. The modified soil-adjusted vegetation index (MSAVI), perpendicular vegetation index (PVI), aspect, elevation, and solar radiation were the key environmental variables affecting soil organic carbon and total nitrogen stocks. In topsoil, remote sensing technology could be used to predict the soil properties in layers; however, as the soil depth increased, the performance of the linear regression models gradually decreased.

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