scholarly journals Relationship between Particulate Matter (PM10) and Airway Inflammation Measured with Exhaled Nitric Oxide Test in Seoul, Korea

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Juwhan Choi ◽  
Jae Kyeom Sim ◽  
Jee Youn Oh ◽  
Young Seok Lee ◽  
Gyu Young Hur ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Regression Analysis ◽  
Particulate Matter ◽  
Linear Regression ◽  
Airway Inflammation ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Exhaled Nitric Oxide ◽  
Healthy People ◽  
Multivariate Linear Regression Analysis

Purpose. Particulate matter (PM) is increasing every year in Asia. It is not fully understood how the airway is affected when inhaling PM. We investigated the correlation between particulate matter with a diameter of less than 10 μm (PM10) and fractional exhaled nitric oxide (FeNO) to determine whether PM causes airway inflammation. Material and Methods. We analyzed patients who visited our outpatient clinic and tested FeNO from January 2016 to December 2017 at the Korea University Guro Hospital. PM10 data were provided by the government of the Republic of South Korea, and measuring station of PM10 is located 800 meters from the hospital. We analyzed the correlation between PM10 and FeNO by a Pearson correlation analysis and by a multivariate linear regression analysis. To identify the most correlated times, we analyzed the correlation between the FeNO and PM10 daily average from the day of visit to 4 days before visit. Results. FeNO positively correlated with PM10 at two days before hospital visit in the Pearson correlation (Pearson correlation coefficient = 0.057; P-value = 0.023) and in the multivariate linear regression analysis (B = 0.051, P-value = 0.026). If the PM10 increased by 100 μg/m3, the FeNO result was expected to rise to 8.3 ppb in healthy people without respiratory disease. Conclusion. The positive correlation was found in both healthy people and asthmatic patients. Therefore, PM10 can increase airway inflammation.

Correlation between FA and ADC, number and length of the periprostatic neurovascular fibers

2021 ◽  
pp. 039156032110637
Author(s):  
Valerio Di Paola ◽  
Angelo Totaro ◽  
Giacomo Avesani ◽  
Benedetta Gui ◽  
Andrea Boni ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Negative Correlation ◽  
Multivariate Regression ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Independent Variables ◽  
Fiber Tracts ◽  
Good Agreement

Purpose: Our aim was to explore the relation between FA and ADC, number and length of the periprostatic neurovascular fibers (PNF) by means of 1.5 T Diffusion Tensor Imaging (DTI) imaging through a multivariate linear regression analysis model. Methods: For this retrospective study, 56 patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including DTI, were enrolled between October 2014 and December 2018. Multivariate regression analysis was performed to evaluate the statistically significant correlation between FA values (dependent variable) and ADC, the number and the length of PNF (independent variables), if p-value <0.05. A value of 0.5 indicated poor agreement; 0.5–0.75, moderate agreement; 0.75–0.9, good agreement; 0.61–0.80, good agreement; and 0.9–1.00, excellent agreement. Results: The overall fit of the multivariate regression model was excellent, with R2 value of 0.9445 ( R2 adjusted 0.9412; p < 0.0001). Multivariate linear regression analysis showed a statistically significant correlation ( p < 0.05) for all the three independent variables. The r partial value was −0.9612 for ADC values ( p < 0.0001), suggesting a strong negative correlation, 0.4317 for the number of fiber tracts ( p < 0.001), suggesting a moderate positive correlation, and −0.306 for the length of the fiber tracts ( p < 0.05), suggesting a weak negative correlation. Conclusions: Our multivariate linear regression model has demonstrated a statistically significant correlation between FA values of PNF with other DTI parameters, in particular with ADC.

scholarly journals Relationship between Thyroid and Kidney Function: Analysis from the Korea National Health and Nutrition Examination Survey Between 2013 and 2015

2020 ◽  
Vol 45 (3) ◽  
pp. 442-454 ◽  
Author(s):  
Sang Hyuk Kim ◽  
Hyang Ki Min ◽  
Sung Woo Lee
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Kidney Function ◽  
Thyroid Function ◽  
Direct Effect ◽  
National Health ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Health And Nutrition

Introduction: Thyroid function is evaluated by thyroid stimulating hormone (TSH) and free thyroxine (fT4). Although many studies have indicated an intimate relationship between thyroid hormones and kidney functions, reports about the simultaneous evaluation of TSH and fT4 are rare. Objective: We aimed to analyze the association between TSH and kidney function, with emphasis on a potential nonlinear relationship, and identify an independent relationship between fT4 and kidney function. Methods: We reviewed the data of 7,061 subjects in the Korea National Health and Nutrition Examination Surveys who were randomly subsampled for thyroid function evaluation between 2013 and 2015. A total of 5,578 subjects were included in the final analysis, after excluding people <18 years old, and those with a short fasting time, abnormal fT4 levels, and thyroid disease or related medications. Creatinine-based estimated glomerular filtration rate (eGFR) was used to define kidney function. Results: A 1 mmol/L increase of logarithmic TSH was associated with decreased eGFR (β: –1.8; 95% CI –2.3 to –1.2; p < 0.001), according to multivariate linear regression analysis. On the multivariate generalized additive model plot, TSH demonstrated an L-shaped relationship with eGFR, showing a steeper slope for 0–4 mIU/L of TSH. A 1 µg/dL increase of fT4 was also associated with decreased eGFR (β: –7.0; 95% CI –0.94 to –4.7; p < 0.001) on the multivariate linear regression analysis; this association was reversed after adjusting for age. On the mediation analysis, the indirect effect via age and direct effect per 1 µg/dL increase of fT4 on eGFR was 9.9 (8.1 to 11.7, p < 0.001) and –7.1 (–9.3 to –4.8, p < 0.001), respectively. Conclusions: Increased TSH was associated with decreased eGFR, particularly in the reference range. The direct effect of increased fT4 was decreased eGFR, which may be affected indirectly by age.

scholarly journals Analysing Enabling Factors Affecting the On-site Productivity in Indian Construction Industry

2018 ◽  
Vol 49 (2) ◽  
pp. 185-193 ◽  
Author(s):  
Saurav Dixit
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Reliability Analysis ◽  
Construction Industry ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Research Paper ◽  
Site Productivity ◽  
Factors Affecting ◽  
Construction Productivity

The growth in construction productivity is low and do not continue for a long span of time. The purpose of the present research paper is to analyse the factors affecting on-site construction productivity in Indian construction industry. The tools used for the analysis are reliability analysis to check the consistency of the data, Pearson correlation analysis to mathematically validate the factor analysis, and linear regression analysis to propose a framework of factors affecting construction productivity. The findings of the reliability analysis concludes that the all the factors having a value of more than 0.67, which is considered to be good for the study, and the findings of the study conclude that the most significant 3 attributes grouped in linear regression analysis change in scope (R2), revision in drawings (R15), and response to change orders (R3) having maximum impact over the construction productivity. The research paper attempts to provide an insight and better understanding of the factors affecting on-site construction productivity in India and the ways and means to control and improve construction productivity of construction projects."This paper is the revised version of the paper that has been published in the proceedings of the Creative Construction Conference 2018: Dixit, S., Mandal, S. N., Thanikal, J. V, & Saurabh, K. (2018). Critical Analysis of Factors Affecting the on-site Productivity in Indian Construction Industry, (July), 38–45. https://doi.org/10.3311/CCC2018-006"

Relative contribution of various expressions of cAMP excretion to other indices of parathyroid function, as tested by discriminant multivariate linear regression analysis.

1986 ◽  
Vol 32 (7) ◽  
pp. 1279-1284 ◽  
Author(s):  
J Valsamis ◽  
J Van Peborgh ◽  
H Brauman
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Adenosine Monophosphate ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Amino Terminal ◽  
Relative Contribution ◽  
Parathyroid Function ◽  
Glomerular Filtrate

Abstract We evaluated the relative contribution to the diagnosis of hyperparathyroid disease from current laboratory indices of parathyroid function--plasma calcium (I), phosphate (II), carboxy-terminal (III) and predominantly amino-terminal (IV) radioimmunoassays of parathyrin, the urinary excretion ratios of cyclic adenosine monophosphate (cAMP) to creatinine (V) or to glomerular filtrate (VI), and the ratio of the nephrogenous fraction of cAMP to glomerular filtrate (VII)--in 224 subjects: 40 with surgically proven hyperparathyroid disease, the others normoparathyroid. The decreasing order of sensitivity was I greater than VI greater than VII greater than V greater than III greater than IV greater than II; all these indices differed significantly between normoparathyroid and hyperparathyroid patients. The decreasing order of specificity was VII, III greater than I greater than IV greater than V, II greater than VI. Discriminant multivariate linear regression analysis was performed in a subset of 58 subjects (17 hyper- and 41 normoparathyroid) from the population studied here, chosen because all of the laboratory indices were determined for each subject. The classification accuracy was 98.3% for combining I, VII, and III (r = 0.908), or I and V (r = 0.893), or I and VII (r = 0.889). The other variables did not add to the precision of classification.

scholarly journals FRAX® Fracture Risks Are Associated with Coronary Artery Calcification Score

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Tzyy-Ling Chuang ◽  
Yi-Da Li ◽  
Fu-Tsung Hsiao ◽  
Mei-Hua Chuang ◽  
Yuh-Feng Wang
Keyword(s):  
Regression Analysis ◽  
Coronary Artery ◽  
Linear Regression ◽  
Fracture Risk ◽  
Coronary Artery Calcification ◽  
Assessment Tool ◽  
Clinical Laboratory ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression Analysis ◽  
Mineral Density

Purpose. To examine the association between fracture risk assessment tool (FRAX) scores and coronary artery calcification (CAC) score in adults. Methods. The medical records of 81 adults who underwent both coronary computed tomography and bone mineral density (BMD) studies in a package during their health exams were reviewed at a regional hospital in Southern Taiwan. Data collected included health history, anthropomorphic characteristics, clinical laboratory results, and BMD. Fracture risk was determined using FRAX. Univariate and multivariate linear regression analysis were used to assess the association between CAC score and 10-year probability of hip fracture (HF) and major osteoporotic fracture (MOF) determined by FRAX. Results. The mean age of the patients was 55.8 years, and 63.0% were male. Univariate linear regression analysis showed that increases in MOF and HF risks, as measured by FRAX, were significantly and positively associated with CAC score. Multiple linear regression analysis adjusting for potential confounders showed that CAC score remained significantly associated with four FRAX indicators, including right MOF (r=0.45, P<0.001), left MOF (r=0.31, P=0.021), right HF (r=0.38, P=0.001), and left HF (r=0.23, P=0.049). Conclusions. Increased risks of MOF and HF as determined by FRAX were significantly and independently associated with CAC score.

scholarly journals Cephalometric Floating Norms as a Guide toward a Harmonious Individual Craniofacial Pattern among Filipinos

2009 ◽  
Vol 79 (6) ◽  
pp. 1162-1168 ◽  
Author(s):  
Marian Almyra Sevilla-Naranjilla ◽  
Ingrid Rudzki-Janson
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Standard Error ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Regression Equations ◽  
Correlated Variables ◽  
The Individual

Abstract Objective: To construct a harmony box based on correlated cephalometric variables, which may serve as a valuable diagnostic tool in orthodontic treatment planning, by analyzing the harmonious relationships of existing individual craniofacial patterns among Filipinos. Materials and Methods: Eighty-one subjects, 37 females and 44 males, were selected from the student population of a University according to established inclusion criteria. Five cephalometric angular measurements were obtained and digitized. Pearson correlation coefficients described the high association among the five variables. The bivariate linear regression analysis was used to construct a harmony box, which contained the cephalometric floating norms of the five correlated variables. Multiple regression analysis and the standard error of the estimate were calculated to construct the harmony schema, which describes the individual craniofacial pattern. Results: Correlations between the five variables were significant at .001 and .05 levels. Linear regression equations with corresponding r2 and standard error of the estimate (SE) were illustrated as the harmony box. The multiple correlation coefficient R, the adjusted R2, and the SE when one of the five measured variables was predicted from the remaining four by means of a multiple regression analysis were displayed as the harmony schema. Conclusion: The cephalometric floating norms describing the individual craniofacial pattern among Filipinos were established based on five correlated variables in the form of a harmony box.

scholarly journals Association Between Bone Mineral Density And Serum Creatinine In People < 46 Years Old

2021 ◽  
Author(s):  
Yanru Guo ◽  
Xianyang Zhu
Keyword(s):  
Bone Mineral Density ◽  
Regression Analysis ◽  
Linear Regression ◽  
Serum Creatinine ◽  
Bone Mineral ◽  
Linear Regression Analysis ◽  
Lumbar Bone Mineral Density ◽  
Multivariate Linear Regression Analysis ◽  
Mineral Density ◽  
The Relationship

Abstract Purpose: To research the relationship between serum creatinine and lumbar bone mineral density in people aged <46 years. Methods: A total of 10,968 subjects from the American Nhanes database were included in this cross-sectional study, including 5,744 males (mean age 26.2 years) and 5224 females (mean age 26.7 years). The exposure factor is the serum creatinine value, and the outcome indicator is the lumbar bone mineral density. This study mainly used multivariate linear regression analysis to test the relationship between lumbar bone mineral density and serum creatinine. Results: In the multivariate linear regression analysis, serum creatinine was positively correlated with lumbar bone mineral density (β = 0.122, 95%CI: 0.047-0.198), but in the subgroup analysis stratified by sex, this positive correlation only exists in the female population (Β = 0.186, 95%CI: 0.070-0.301).Conclusions: Our study found that in women aged <46 years with normal renal function, there is a positive correlation between serum creatinine and lumbar BMD. And in those people, the determination of serum creatinine can provide a sensitive biomarker for the early identification and treatment of Osteopenia or osteoporosis.

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