scholarly journals Effects of Maternal Homelessness, Supplemental Nutrition Programs, and Prenatal PM2.5 on Birthweight

2019 ◽  
Vol 16 (21) ◽  
pp. 4154 ◽  
Author(s):  
Jongeun Rhee ◽  
M. Patricia Fabian ◽  
Stephanie Ettinger de Cuba ◽  
Sharon Coleman ◽  
Megan Sandel ◽  
...  
Keyword(s):  
Synergistic Effects ◽  
Fine Particulate Matter ◽  
Black Mothers ◽  
Second Trimester ◽  
Linear Regression Models ◽  
Supplemental Nutrition ◽  
Nutrition Programs ◽  
Wic Participation ◽  
Pollution Exposure ◽  
The Impact

Few studies examined the impact of maternal socioeconomic status and of its combined effects with environmental exposures on birthweight. Our goal was to examine the impact of maternal homelessness (mothers ever homeless or who lived in shelters during pregnancy) and participation in the Special Supplemental Nutrition Program for Women, Infants and Children (WIC) during pregnancy in conjunction with air pollution exposure on birthweight in the Boston-based Children’s HealthWatch cohort from 2007 through 2015 (n = 3366). Birthweight was obtained from electronic health records. Information on maternal homelessness and WIC participation during pregnancy were provided via a questionnaire. Prenatal fine particulate matter (PM2.5) exposures, estimated at the subject’s residential address, were calculated for each trimester. We fit linear regression models adjusting for maternal and child characteristics, seasonality, and block-group-level median household income and examined the interactions between PM2.5 and each covariate. Prenatal maternal homelessness was associated with reduced birthweight (−55.7 g, 95% CI: −97.8 g, −13.7 g), while participating in WIC was marginally associated with increased birthweight (36.1 g, 95% CI: −7.3 g, 79.4 g). Only average PM2.5 during the second trimester was marginally associated with reduced birthweight (−8.5 g, 95% CI: −19.3, 2.3) for a 1 µg/m3 increase in PM2.5. The association of PM2.5 during the second trimester with reduced birthweight was stronger among non-Hispanic Black mothers and trended toward significance among immigrants and single mothers. Our study emphasizes the independent and synergistic effects of social and environmental stressors on birthweight, particularly the potentially protective effect of participating in WIC for vulnerable populations.

scholarly journals Long-term air pollution exposure and incident dementia in American elderly population: a national cohort study (2000-2018)

2021 ◽  
Author(s):  
Liuhua Shi ◽  
Kyle Steenland ◽  
Haomin Li ◽  
Pengfei Liu ◽  
Yuhan Zhang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Healthy Aging ◽  
Fine Particulate Matter ◽  
Warm Season ◽  
Population Based ◽  
Incident Dementia ◽  
Air Pollution Exposure ◽  
Pollution Exposure ◽  
The Impact

Abstract Epidemiological evidence suggests air pollution exposure may increase risk of Alzheimer’s disease and related dementias (ADRD). However, previous U.S. studies have predominantly focused on hospitalizations, which fails to fully capture ADRD. Here we constructed two national population-based cohorts of those aged 65 and above from the Medicare Chronic Conditions Warehouse (2000-2018), including doctor visits, to investigate the impact of long-term exposure to ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) on dementia and AD incidence, respectively. We identified ~2.0 million incident dementia cases (N=12,233,371; dementia cohort) and ~0.8 million incident AD cases (N=12,456,447; AD cohort). Per interquartile range (IQR) increase in the 5-year average PM2.5 (3.2 µg/m3), NO2 (11.6 ppb), and warm-season O3 (5.3 ppb) over the past 5 years prior to diagnosis, the hazard ratios (HRs) were 1.060 (95% confidence interval [CI]: 1.054, 1.066), 1.019 (95% CI: 1.012, 1.026), and 0.990 (95% CI: 0.987, 0.993) for incident dementias, and 1.078 (95% CI: 1.070, 1.086), 1.031 (95% CI: 1.023, 1.039), and 0.982 (95%CI: 0.977, 0.986) for incident AD, respectively, for the three pollutants. For both outcomes there was strong evidence of linearity in concentration-response relationships for PM2.5 and NO2, suggesting the lack of a clear safe threshold for these health-harmful pollutants. Our study suggests that exposures to PM2.5 and NO2, but not O3, may increase the incidence of dementia and AD. Improving air quality may reduce the burden of ADRD and promote healthy aging.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

INFLUENCE OF GREENHOUSE SHADING AND DIFFERENT NUTRIENT MANAGEMENT PRACTICES ON ALLEVIATING HEAT STRESS, IMPROVING PLANT NUTRIENTS STATUS, FLOWERING GROWTH AND YIELD OF TOMATO

2020 ◽  
Vol 51 (4) ◽  
pp. 1001-1014
Author(s):  
Sulaiman & Sadiq
Keyword(s):  
Heat Stress ◽  
Management Practices ◽  
Nutrient Management ◽  
Block Design ◽  
Nutrient Status ◽  
Growth And Yield ◽  
Reproductive Growth ◽  
Positive Effects ◽  
Nutrition Programs ◽  
The Impact

The experiment was conducted in a greenhouse during 2017 and 2018 growing seasons to evaluate the impact of the shading and various nutrition programs on mitigating heat stress, reducing the use of chemical minerals, improving the reproductive growth and yield of tomato plant. Split-plot within Randomized Complete Block Design (RCBD) with three replications was conducted in this study. Shading factor was allocated in the main plots and the nutrition programs distributed randomly in the subplots. Results indicate that shading resulted in the decrease of daytime temperature by 5.7˚C as an average for both seasons; thus a significant increasing was found in leaf contents of macro nutrients (Nitrogen, Phosphorous, and Potassium), and micro nutrients (Iron, Zinc and Boron), except the Iron content in 2018 growing season. Furthermore, shading improved significantly the reproductive growth and tomato yield. Among the plant nutrition programs, the integrated nutrient management (INM) including the application of organic substances, bio inoculum of AMF and 50% of the recommended dose of chemical fertilizers; lead to the enhancement of nutrients content, reproductive characteristics and plant yield. Generally, combination of both shading and INM showed positive effects on plants nutrient status and persisting balance on tomato flowering growth and fruits yield.

Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

scholarly journals Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

2021 ◽  
pp. 193229682110123
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Pratik Choudhary ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
Open Loop ◽  
Random Errors ◽  
Linear Regression Models ◽  
Reference Case ◽  
Counting Error ◽  
The Impact

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

Impact of 24/7 Onsite Emergency Radiology Staff Coverage on Emergency Department Workflow

2021 ◽  
pp. 084653712110238
Author(s):  
Francesco Macri ◽  
Bonnie T. Niu ◽  
Shannon Erdelyi ◽  
John R. Mayo ◽  
Faisal Khosa ◽  
...  
Keyword(s):  
Emergency Department ◽  
Major Trauma ◽  
Patient Flow ◽  
Interrupted Time Series ◽  
Trauma Patients ◽  
Linear Regression Models ◽  
High Acuity ◽  
Time Series Approach ◽  
Comparison Series ◽  
The Impact

Purpose: Assess the impact of 24/7/365 emergency trauma radiology (ETR) coverage on Emergency Department (ED) patient flow in an urban, quaternary-care teaching hospital. Methods: Patient ED visit and imaging information were extracted from the hospital patient care information system for 2008 to 2018. An interrupted time-series approach with a comparison group was used to study the impact of 24/7/365 ETR on average monthly ED length of stay (ED-LOS) and Emergency Physician to disposition time (EP-DISP). Linear regression models were fit with abrupt and permanent interrupts for 24/7/365 ETR, a coefficient for comparison series and a SARIMA error term; subgroup analyses were performed by patient arrival time, imaging type and chief complaint. Results: During the study period, there were 949,029 ED visits and 739,796 diagnostic tests. Following implementation of 24/7/365 coverage, we found a significant decrease in EP-DISP time for patients requiring only radiographs (-29 min;95%CI:-52,-6) and a significant increase in EP-DISP time for major trauma patients (46 min;95%CI:13,79). No significant change in patient throughput was observed during evening hours for any patient subgroup. For overnight patients, there was a reduction in EP-DISP for patients with symptoms consistent with stroke (-78 min;95%CI:-131,-24) and for high acuity patients who required imaging (-33 min;95%CI:-57,-10). Changes in ED-LOS followed a similar pattern. Conclusions: At our institution, 24/7/365 in-house ETR staff radiology coverage was associated with improved ED flow for patients requiring only radiographs and for overnight stroke and high acuity patients. Major trauma patients spent more time in the ED, perhaps reflecting the required multidisciplinary management.

scholarly journals Non-Parametric Generalized Additive Models as a Tool for Evaluating Policy Interventions

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 299
Author(s):  
Jaime Pinilla ◽  
Miguel Negrín
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Trend ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Linear Regression Models ◽  
Non Linear ◽  
Nonlinear Trends ◽  
The Impact ◽  
Non Parametric

The interrupted time series analysis is a quasi-experimental design used to evaluate the effectiveness of an intervention. Segmented linear regression models have been the most used models to carry out this analysis. However, they assume a linear trend that may not be appropriate in many situations. In this paper, we show how generalized additive models (GAMs), a non-parametric regression-based method, can be useful to accommodate nonlinear trends. An analysis with simulated data is carried out to assess the performance of both models. Data were simulated from linear and non-linear (quadratic and cubic) functions. The results of this analysis show how GAMs improve on segmented linear regression models when the trend is non-linear, but they also show a good performance when the trend is linear. A real-life application where the impact of the 2012 Spanish cost-sharing reforms on pharmaceutical prescription is also analyzed. Seasonality and an indicator variable for the stockpiling effect are included as explanatory variables. The segmented linear regression model shows good fit of the data. However, the GAM concludes that the hypothesis of linear trend is rejected. The estimated level shift is similar for both models but the cumulative absolute effect on the number of prescriptions is lower in GAM.

scholarly journals Profile of the Change in Depression during Proton-Pump Inhibitor Therapy in Patients with Gastroesophageal Reflux Disease: Influence of the Mucosal Break

2021 ◽  
Vol 18 (11) ◽  
pp. 5964
Author(s):  
Chia-Liang Wu ◽  
Chien-Lin Chen ◽  
Shu-Hui Wen
Keyword(s):  
Gastroesophageal Reflux Disease ◽  
Gastroesophageal Reflux ◽  
Proton Pump ◽  
Reflux Disease ◽  
Proton Pump Inhibitor Therapy ◽  
Linear Regression Models ◽  
Independent Variable ◽  
The Difference ◽  
Mucosal Break ◽  
The Impact

Given the frequent concomitance between depression and gastroesophageal reflux disease (GERD), it is important to evaluate the change of depression in patients with GERD, especially considering the presence of esophageal mucosal breaks (MB). This study aimed to examine the change in the levels of depression in patients with GERD during proton-pump inhibitors (PPI) therapy. We designed a prospective cohort study to explore the profile of the alteration in depression with respect to the impact of esophageal MB. This study recruited 172 eligible patients with GERD between February 2016 and May 2018. The change in depression was defined as the difference between the respective Taiwanese Depression Questionnaire (TDQ) scores obtained at baseline and after PPI therapy. Multivariate linear regression models were used to estimate the factors associated with the change in depression. The results revealed statistically significant improvements in the TDQ score (mean score: baseline = 13.2, after PPI therapy = 10.9, p < 0.01, Cohen’s d = 0.30) during PPI therapy for GERD. Moreover, the MB was an independent variable associated with changes in the TDQ score [B = 3.31, 95% confidence interval (CI): (1.12, 5.51), p < 0.01] and the improvement in depression [odds ratio = 0.38, 95% CI: (0.17, 0.86), p = 0.02]. Our findings revealed that depressive symptoms improved slightly following PPI therapy. Moreover, MB was an unfavorable prognostic factor for the improvement in depression.

scholarly journals Socioeconomic Status Moderates the Impact of Emotional but not Physical Childhood Abuse on Women’s Sleep

2021 ◽  
Author(s):  
Cheryl L. Currie ◽  
Erin K. Higa ◽  
Lisa-Marie Swanepoel
Keyword(s):  
Socioeconomic Status ◽  
Child Abuse ◽  
Sleep Quality ◽  
Childhood Abuse ◽  
Emotional Abuse ◽  
Linear Regression Models ◽  
Physical Child Abuse ◽  
Moderating Variables ◽  
Childhood Socioeconomic Status ◽  
The Impact

AbstractA recent systematic review highlighted associations between childhood abuse and adult sleep quality, and the need for research focused specifically on women and the role of moderating variables. The objectives of the present study were (1) to assess the impact of frequent physical and emotional child abuse on adult sleep among women; and (2) to assess the role that childhood socioeconomic status (SES) could play in moderating these associations. In-person data were collected from women living in a mid-sized city in western Canada in 2019–2020 (N = 185; M age = 40 years). Sleep quality was measured using the Pittsburgh Sleep Quality Index. Physical and emotional abuse experienced often or very often in childhood were assessed using single items (yes or no). Childhood SES was assessed by a single item and dichotomized at the sample median. Linear regression models examined associations between each form of abuse and continuous adult sleep quality score adjusted for covariates. Statistically significant interactions were stratified and examined by child SES group. Frequent physical and emotional childhood abuse were each associated with clinically and statistically significant increases in past-month sleep problem scores among women in adjusted models. This association was moderated by childhood SES for emotional child abuse, but not physical child abuse. Findings suggest that growing up in an upper-middle to upper SES household may buffer the adverse impact of frequent emotional child abuse on later adult sleep, but may not promote resilience in the context of frequent physical child abuse. 

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