Physiological Aldosterone Concentrations Are Associated with Alterations of Lipid Metabolism: Observations from the General Population

International Journal of Endocrinology ◽

10.1155/2018/4128174 ◽

2018 ◽

Vol 2018 ◽

pp. 1-6 ◽

Cited By ~ 6

Author(s):

M. Hannich ◽

H. Wallaschofski ◽

M. Nauck ◽

M. Reincke ◽

C. Adolf ◽

...

Keyword(s):

Lipid Metabolism ◽

General Population ◽

Linear Regression ◽

Standard Error ◽

Regression Models ◽

Adult Population ◽

Density Lipoprotein ◽

Lipoprotein Cholesterol ◽

Inverse Association ◽

Linear Regression Models

Objective. Aldosterone and high-density lipoprotein cholesterol (HDL-C) are involved in many pathophysiological processes that contribute to the development of cardiovascular diseases. Previously, associations between the concentrations of aldosterone and certain components of the lipid metabolism in the peripheral circulation were suggested, but data from the general population is sparse. We therefore aimed to assess the associations between aldosterone and HDL-C, low-density lipoprotein cholesterol (LDL-C), total cholesterol, triglycerides, or non-HDL-C in the general adult population. Methods. Data from 793 men and 938 women aged 25–85 years who participated in the first follow-up of the Study of Health in Pomerania were obtained. The associations of aldosterone with serum lipid concentrations were assessed in multivariable linear regression models adjusted for sex, age, body mass index (BMI), estimated glomerular filtration rate (eGFR), and HbA1c. Results. The linear regression models showed statistically significant positive associations of aldosterone with LDL-C (β-coefficient = 0.022, standard error = 0.010, p=0.03) and non-HDL-C (β-coefficient = 0.023, standard error = 0.009, p=0.01) as well as an inverse association of aldosterone with HDL-C (β-coefficient = −0.022, standard error = 0.011, p=0.04). Conclusions. The present data show that plasma aldosterone is positively associated with LDL-C and non-HDL-C and inversely associated with HDL-C in the general population. Our data thus suggests that aldosterone concentrations within the physiological range may be related to alterations of lipid metabolism.

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Evaluation of standard error of forecast of runoff volume using linear regression models

Canadian Journal of Civil Engineering ◽

10.1139/l02-055 ◽

2002 ◽

Vol 29 (5) ◽

pp. 635-640 ◽

Cited By ~ 4

Author(s):

Wuben Luo ◽

Eric Weiss

Keyword(s):

Linear Regression ◽

Standard Error ◽

Regression Models ◽

Linear Regression Models ◽

Modeling Error ◽

Reservoir Operations ◽

Microsoft Excel ◽

Runoff Volume ◽

Modeling Errors ◽

Significant Underestimation

Optimizing reservoir operations requires forecasts of seasonal inflow and a good understanding of the associated uncertainties. When forecasting seasonal runoff volume to a reservoir using a linear regression model, hydrologic forecasters typically use the standard error of residuals as the standard error of forecast to give water managers a sense of uncertainties in the forecast. However, this practice accounts for only the random error and ignores the modeling error in the volume forecast, resulting in underestimation of the standard error of the forecast. The underestimation can become significant in extreme runoff years for which reservoir operations tend to be most critical. This paper presents the algorithm for calculating the standard error of forecast, which takes into consideration both random and modeling errors. A simple way of calculating the standard error of forecast using built-in functions in Microsoft Excel is described. An example is used to demonstrate the potentially significant underestimation of the true error of a forecast if modeling error is ignored.Key words: standard error of forecast, residuals, runoff volume forecast, regression analysis.

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Seasonal Polymorphism in Elytral Coloration Pattern of Anomala flavipennis Burmeister (Coleoptera: Scarabaeidae) in Mexico

Journal of Entomological Science ◽

10.18474/0749-8004-39.4.545 ◽

2004 ◽

Vol 39 (4) ◽

pp. 545-550 ◽

Cited By ~ 1

Author(s):

Luis A. Rodríguez-del-Bosque

Keyword(s):

Linear Regression ◽

Significant Interaction ◽

Regression Models ◽

Inverse Association ◽

Linear Regression Models ◽

Weighted Mean ◽

Coloration Pattern ◽

Northeastern Mexico ◽

Coloration Patterns

Elytral polychromatism in Anomala flavipennis Burmeister was detected in both spring and fall generations in northeastern Mexico from 2000 to 2002. Four distinctive coloration patterns were observed: (a) immaculated, (b) one-spotted, (c) two-spotted, and (d) striped. These categories were represented by 0, 1.4, 7.8, and 28.0% respective levels of melanization of elytral area. A significant interaction was detected between elytral pattern and generation, with melanized forms occurring more commonly during the spring and clearer forms during the fall. Weighted mean of elytral melanized area in the population ranged from 1.46% for fall to 7.80% for spring generations. Linear regression models suggested (R2 ≥ 0.93) an inverse association between temperature during pupation-adult ecdysis and elytral melanized area. The rationale and advantage for A. flavipennis responding to temperature by elytral melanization remain unknown, particularly because of the crepuscular-nocturnal habits of adults.

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Investigating Students’ Difficulties in Understanding Confidence Intervals in Linear Regression Models

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.33.23485 ◽

2018 ◽

Vol 7 (4.33) ◽

pp. 60

Author(s):

Nor Rashidah Paujah @ Ismail ◽

Fadzilah Abdol Razak ◽

Norhayati Baharun

Keyword(s):

Linear Regression ◽

Confidence Interval ◽

Confidence Intervals ◽

Standard Error ◽

Regression Models ◽

Degrees Of Freedom ◽

Good Explanation ◽

Correct Interpretation ◽

Linear Regression Models ◽

Regression Slope

How do tertiary students perform when finding confidence intervals of linear regression models? Do they have strong understanding on how to compute the interval and provide good explanation on the interval obtained? To answer these questions, 197 answer scripts were examined to investigate students’ ability to calculate the confidence interval of the regression slope and their ability to make comprehensive interpretation afterwards. It was found that only 48% of the students managed to compute the confidence interval correctly. The errors made by most of the students were caused by the failure to identify the correct degrees of freedom and the failure to evaluate the correct value of the standard error of the slope. Of those who were able to compute the correct values, the percentage that were able to give complete and correct interpretation dropped to only 7.1%. 68.5% of them provided incorrect interpretations which showed their inability to understand the concept of regression slope. It is hoped that this study will give some ideas to educators in providing better understanding on computing and interpreting the confidence interval among students.

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Abstract P221: Plasma Triglyceride/High Density Lipoprotein Cholesterol Ratio and Subclinical Cardiovascular Disease Parameters in a South Asian Population

Circulation ◽

10.1161/circ.131.suppl_1.p221 ◽

2015 ◽

Vol 131 (suppl_1) ◽

Author(s):

Mohan Thanikachalam ◽

Jahnavi Sunderarajan ◽

Shravanti Shankar ◽

Vijaykumar Harivanzan ◽

Sadagopan Thanikachalam

Keyword(s):

Cardiovascular Disease ◽

Linear Regression ◽

High Density Lipoprotein ◽

South Asian ◽

Regression Models ◽

Density Lipoprotein ◽

Asian Population ◽

High Density ◽

Linear Regression Models ◽

South Asian Population

Background: There is increasing focus on biomarkers for early detection of cardiovascular disease (CVD). Studies suggest that the ratio of triglyceride (TG)/high density lipoprotein (HDL) could be a simple marker for insulin resistant and increased cardiometabolic risk, but the association between TG/HDL ratio and CVD is not fully defined. In the current study we assess the relationship between TG/HDL ratio and subclinical CVD parameters in a South Asian population. Methods: In the cross-sectional analysis of 8080 South Indians, the assessments included left ventricular mass indexed (LVMI) to body surface area by echocardiograph, carotid intimal medial thickness (IMT), arterial stiffness by carotid-femoral pulse wave velocity (PWV) and endothelial function by brachial artery flow mediated dilatation (FMD). Generalized linear regression models were used to test the association of TG/HGL ratio with subclinical parameters. All models were adjusted for age, gender, BMI, physical activity, LDL, blood sugar, smoking, stress, and anxiety status. Results: After the exclusion of people with evidence of coronary artery disease, 7164 subjects (mean age 43 years, 58% women) constituted the study sample. The value of subclinical parameters by TG/HDL quartiles is shown in the Table. In univariate analysis, TG/HDL ratio was associated with subclinical parameters [PWV (r = 0.14), LVMI (r = 0.11), FMD (r = -0.06); IMT (r = 0.103; p <0.01]. In adjusted linear regression models, TG/HDL ratio was independently associated with PWV (β = 0.029, p = 0.014) and IMT (β = 0.051, p <0.01). Subsequently, in gender specific models, TG/HDL ratio was independently associated PWV and IMT only in women [PWV (β = 0.042, p = 0.006); IMT (β = 0.067, p = 0.01)] and in subgroup analysis in healthy participants below 40 years of age [PWV (β = 0.082, p <0.01); IMT (β= 0.067, p = 0.01)]. Conclusion: TG/HDL ratio was independently associated with PWV and IMT in South Asian women, including apparently health young individuals.

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Fatigue in newly diagnosed acute myeloid leukaemia: general population comparison and predictive factors

BMJ Supportive & Palliative Care ◽

10.1136/bmjspcare-2020-002312 ◽

2021 ◽

pp. bmjspcare-2020-002312

Author(s):

Laura B Oswald ◽

Adriano Venditti ◽

David Cella ◽

Francesco Cottone ◽

Anna Candoni ◽

...

Keyword(s):

General Population ◽

Linear Regression ◽

Acute Myeloid Leukaemia ◽

Regression Models ◽

Disease Risk ◽

Newly Diagnosed ◽

Linear Regression Models ◽

Mean Differences ◽

Risk Categories ◽

Acute Myeloid

ObjectivesThis study compared the burden of fatigue between treatment-naïve patients with newly diagnosed acute myeloid leukaemia (AML) and the general population and investigated patient factors associated with fatigue severity.MethodsPretreatment patient-reported fatigue was assessed with the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire in a sample of 463 newly diagnosed patients with AML who were enrolled in a clinical trial. Multivariable linear regression models were used to estimate the adjusted mean differences in fatigue between patients with AML and adults from the general population (n=847) by AML disease risk categories. A clinically meaningful difference in fatigue was defined as ≥3 points. Univariable and multivariable linear regression models were used to identify sociodemographic, clinical and molecular correlates of worse fatigue in patients with AML.ResultsPatients with AML reported adjusted mean fatigue scores that were 7.5 points worse than the general population (95% CI −8.6 to −6.4, p<0.001). Across AML disease risk categories, adjusted mean differences in fatigue compared with the general population ranged from 6.7 points worse (patients with favourable risk: 95% CI −8.6 to −4.8, p<0.001) to 8.9 points worse (patients with poor risk, 95% CI −10.5 to −7.2, p<0.001). Overall, 91% of patients with AML reported fatigue that was equal to or worse than the general population’s median fatigue score. Higher pretreatment fatigue was independently associated with female sex, WHO performance status ≥1 and lower platelet levels.ConclusionsPatients with newly diagnosed AML reported worse fatigue than the general population, and mean differences exceeded twice the threshold for clinical significance. Our findings may help to identify patients with AML most likely to benefit from supportive care interventions to reduce fatigue.

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P2500The high-sensitivity cardiac troponin I and T response following strenuous activity is attenuated by smokeless tobacco:The North Sea Race Endurance Exercise Study (NEEDED) 2014

European Heart Journal ◽

10.1093/eurheartj/ehz748.0829 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

J Skranes ◽

O Kleiven ◽

K M Aakre ◽

O Skadberg ◽

T H Melberg ◽

...

Keyword(s):

General Population ◽

Linear Regression ◽

North Sea ◽

Troponin I ◽

Low Density Lipoprotein ◽

Linear Regression Analysis ◽

Density Lipoprotein ◽

High Sensitivity ◽

Tobacco Product ◽

Linear Regression Models

Abstract Background Use of snus, a smokeless oral tobacco product, is increasing among athletes and recreational exercisers in Scandinavia. Strenuous physical activity is associated with an acute increase in high-sensitivity cardiac troponins (hs-cTn) in healthy individuals. Current smoking is associated with lower baseline hs-cTn concentrations in current smokers in the general population, but whether tobacco affects the hs-cTn response to exercise remains unknown. Methods We measured serial cTnI and cTnT concentrations in 1002 healthy recreational athletes before, 3 and 24 h after a 91 km bicycle race. Self-reported snus habits were reported as: non-current (n=794) and current (n=118). The association between snus use and change in log hs-cTnI and hs-cTnT (differences between concentrations at baseline and 3 h (Δ3 h) and 24 h (Δ24 h)) were assessed by multivariable linear regression analysis. Results Current snus use was associated with lower cTnI (current users of snus vs non-current: median, 1.7 ng/l; interquartile range (IQR), 1.6–2.3 vs 2.0 ng/L; IQR 1.6–3.2; p=0.020) and cTnT (current users of snus vs non-current: median, 3.0 ng/L, IQR, 3.0–3.5 vs 3.0 ng/L, IQR 3.0–4.3; p=0.021) concentrations at baseline. Both in unadjusted and fully adjusted linear regression models, users of snus had significantly lower Δ3 h and Δ24 h cTnI and cTnT concentrations (Table). Association between snus use and change in concentrations of hs-cTnI and hs-cTnT (95% CI) Model 1 Model 2 Model 3 Model 4 ΔcTnI 3 h Current snus −28% (−46% to −10%), p=0.003 −33% (−51% to −14%), p=0.001 −31% (−49% to −13%), p=0.001 −29% (−47% to −11%), p=0.002 ΔcTnI 24 h Current snus −38% (−62% to −15%), p=0.002 −36% (−59% to −12%), p=0.003 −32% (−56% to −9%), p=0.007 −30% (−54% to −7%), p=0.010 ΔcTnT 3 h Current snus −28% (−10% to −46%), p=0.003 −33% (−51% to −14%), p=0.001 −31% (−49% to −13%), p=0.001 −29% (−47% to −11%), p=0.002 ΔcTnT 24 h Current snus −20% (−4% to −36%), p=0.015 −23% (−39% to −8%), p=0.004 −21% (−36% to −5%), p=0.009 −19% (−34% to −14%), p=0.013 Model 1 unadjusted; Model 2 adjusted for sex and age; Model 3 adjusted for Model 2 and systolic blood pressure, body mass index, low-density lipoprotein and estimated glomerular filtration rate; Model 4 adjusted for the same variables as in Model 3 but also race duration and resting heart rate. Conclusion The exercise-induced cTn response in healthy recreational cyclist is attenuated in users of smokeless tobacco compared to never users. These findings extend observations of lower hs-cTn concentrations in tobacco smokers in the general population. Acknowledgement/Funding Operating grant from North Sea Race, Abbot Diagnostics, Lærdal Foundation. PhD fellowship from South-Eastern Norway Regional Health Authority.

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High-density Lipoprotein Cholesterol Is Negatively Correlated with Bone Mineral Density and Has Potential Predictive Value for Bone Loss

Lipids in Health and Disease ◽

10.1186/s12944-021-01497-7 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Yuchen Tang ◽

Shenghong Wang ◽

Qiong Yi ◽

Yayi Xia ◽

Bin Geng

Keyword(s):

Bone Mineral Density ◽

Linear Regression ◽

Regression Models ◽

Generalized Additive Models ◽

Density Lipoprotein ◽

Additive Models ◽

Nonlinear Relationship ◽

Linear Regression Models ◽

Mineral Density ◽

Increased Risk

Abstract Background Many studies have shown that lipids play important roles in bone metabolism. However, the association between high-density lipoprotein cholesterol (HDL-C) and bone mineral density (BMD) is unclear. Therefore, this study aimed to investigate the linear or nonlinear relation between HDL-C levels and BMD and addressed whether the HDL-C levels had the potential values for predicting the risk of osteoporosis or osteopenia. Methods Two researchers independently extracted all information from the National Health and Nutrition Examination Survey (NHANES) database. Participants over 20 years of age with available HDL-C and BMD data were enrolled in the final analysis. The linear relationship between HDL-C levels and BMD was assessed using multivariate linear regression models. Moreover, the nonlinear relationship was also characterized by fitted smoothing curves and generalized additive models. In addition, the odds ratio (OR) for osteopenia and osteoporosis was evaluated with multiple logistic regression models. Results The weighted multivariable linear regression models demonstrated that HDL-C levels displayed an inverse association with BMD, especially among females and subjects aged 30 to 39 or 50 to 59. Moreover, the nonlinear relationship characterized by smooth curve fittings and generalized additive models suggested that (i) HDL-C levels displayed an inverted U-shaped relationship with BMD among women 30 to 39 or over 60 years of age; (ii) HDL-C levels exhibited a U-shaped association with BMD among women 20 to 29 or 50 to 59 years of age. In addition, females with high HDL levels (62-139 mg/dL) had an increased risk of osteopenia or osteoporosis. Conclusion This study demonstrated that HDL-C levels exhibit an inverse correlation with BMD. Especially in females, clinicians need to be alert to patients with high HDL-C levels, which may indicate an increased risk of osteoporosis or osteopenia. For these patients, close monitoring of BMD and early intervention may be necessary.

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FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

Journal of Business Economics ◽

10.35760/eb.2018.v23i1.1812 ◽

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.

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