Does micronutrients intake modulate the risk of coronary heart disease?

2019 ◽  
Vol 49 (3) ◽  
pp. 368-380 ◽  
Author(s):  
Mohammed Azab ◽  
Abdel-Ellah Al-Shudifat ◽  
Lana Agraib ◽  
Sabika Allehdan ◽  
Reema Tayyem
Keyword(s):  
Coronary Heart Disease ◽  
Logistic Regression ◽  
Heart Disease ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Daily Intake ◽  
Dietary Intakes ◽  
Content Type ◽  
Study Results

Purpose The purpose of this study was to examine the relationship between micronutrient intake and coronary heart disease (CHD) in middle-aged Jordanian participants. Design/methodology/approach A case-control study was conducted among patients referring for elective coronary angiography. A total of 400 patients were enrolled in this study. Face-to-face interview was used to complete food frequency questionnaire from which the authors derived usual daily intake of micronutrients. The mean age of participates was 52 years and their average BMI was 30.7 kg/m2. Multinomial logistic regression model and linear logistic regression model were used to calculate odd ratios (OR) and its 95 per cent confidence interval (CI) and p-value for trend, respectively. The association between the risk of CHD and micronutrients intake was adjusted for the age, gender, BMI, smoking, physical activity, total energy intake, occupation, education level, marital status and family history. Findings The study results showed no significant differences between cases and controls for dietary intakes of micronutrients, except for the intake of calcium (p < 0.005), magnesium (p < 0.025), phosphorus (p < 0.023) and potassium (p < 0.006) which were lower in cases than controls. Although no significant trend was observed between most of the dietary intake of micronutrients and the risk of developing CHD, a significant protective effect of magnesium [OR 0.52; 95 per cent CI (0.29-0.95)], phosphorus [OR 0.44; 95 per cent CI (0.24-0.80)] and potassium [OR 0.41; 95 per cent CI (0.22-0.74)] against the risk of CHD was detected. Originality/value The findings from this study provide strong evidence that the intake of micronutrients such as calcium, magnesium, phosphorus and potassium has no significant associations with the risk of CHD.

scholarly journals Exploring the diagnostic effectiveness for myocardial ischaemia based on CCTA myocardial texture features

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hengyu Zhao ◽  
Lijie Yuan ◽  
Zhishang Chen ◽  
Yuting Liao ◽  
Jiangzhou Lin
Keyword(s):  
Coronary Heart Disease ◽  
Logistic Regression ◽  
Heart Disease ◽  
Regression Model ◽  
Myocardial Ischaemia ◽  
Logistic Regression Model ◽  
Texture Features ◽  
Spearman Correlation ◽  
Multivariable Logistic Regression Model ◽  
Training Cohort

Abstract Background To explore the characteristics of myocardial textures on coronary computed tomography angiography (CCTA) images in patients with coronary atherosclerotic heart disease, a classification model was established, and the diagnostic effectiveness of CCTA for myocardial ischaemia patients was explored. Methods This was a retrospective analysis of the CCTA images of 155 patients with clinically diagnosed coronary heart disease from September 2019 to January 2020, 79 of whom were considered positive (myocardial ischaemia) and 76 negative (normal myocardial blood supply) according to their clinical diagnoses. By using the deep learning model-based CQK software, the myocardium was automatically segmented from the CCTA images and used to extract texture features. All patients were randomly divided into a training cohort and a test cohort at a 7:3 ratio. The Spearman correlation and least absolute shrinkage and selection operator (LASSO) method were used for feature selection. Based on the selected features of the training cohort, a multivariable logistic regression model was established. Finally, the test cohort was used to verify the regression model. Results A total of 387 features were extracted from the CCTA images of the 155 coronary heart disease patients. After performing dimensionality reduction with the Spearman correlation and LASSO, three texture features were selected. The accuracy, area under the curve, specificity, sensitivity, positive predictive value and negative predictive value of the constructed multivariable logistic regression model with the test cohort were 0.783, 0.875, 0.733, 0.875, 0.650 and 0.769, respectively. Conclusion CCTA imaging texture features of the myocardium have potential as biomarkers for diagnosing myocardial ischaemia.

scholarly journals A comprehensive, contemporary assessment of the association between hepatosteatosis and coronary artery calcium scoring

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
T Heseltine ◽  
SW Murray ◽  
RL Jones ◽  
M Fisher ◽  
B Ruzsics
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Coronary Artery ◽  
Regression Model ◽  
Coronary Artery Calcium ◽  
Logistic Regression Model ◽  
Prediction Models ◽  
Multinomial Logistic Regression ◽  
Cvd Risk ◽  
Male Sex

Abstract Funding Acknowledgements Type of funding sources: None. onbehalf Liverpool Multiparametric Imaging Collaboration Background Coronary artery calcium (CAC) score is a well-established technique for stratifying an individual’s cardiovascular disease (CVD) risk. Several well-established registries have incorporated CAC scoring into CVD risk prediction models to enhance accuracy. Hepatosteatosis (HS) has been shown to be an independent predictor of CVD events and can be measured on non-contrast computed tomography (CT). We sought to undertake a contemporary, comprehensive assessment of the influence of HS on CAC score alongside traditional CVD risk factors. In patients with HS it may be beneficial to offer routine CAC screening to evaluate CVD risk to enhance opportunities for earlier primary prevention strategies. Methods We performed a retrospective, observational analysis at a high-volume cardiac CT centre analysing consecutive CT coronary angiography (CTCA) studies. All patients referred for investigation of chest pain over a 28-month period (June 2014 to November 2016) were included. Patients with established CVD were excluded. The cardiac findings were reported by a cardiologist and retrospectively analysed by two independent radiologists for the presence of HS. Those with CAC of zero and those with CAC greater than zero were compared for demographic and cardiac risks. A multivariate analysis comparing the risk factors was performed to adjust for the presence of established risk factors. A binomial logistic regression model was developed to assess the association between the presence of HS and increasing strata of CAC. Results In total there were 1499 patients referred for CTCA without prior evidence of CVD. The assessment of HS was completed in 1195 (79.7%) and CAC score was performed in 1103 (92.3%). There were 466 with CVD and 637 without CVD. The prevalence of HS was significantly higher in those with CVD versus those without CVD on CTCA (51.3% versus 39.9%, p = 0.007). Male sex (50.7% versus 36.1% p= &lt;0.001), age (59.4 ± 13.7 versus 48.1 ± 13.6, p= &lt;0.001) and diabetes (12.4% versus 6.9%, p = 0.04) were also significantly higher in the CAC group compared to the CAC score of zero. HS was associated with increasing strata of CAC score compared with CAC of zero (CAC score 1-100 OR1.47, p = 0.01, CAC score 101-400 OR:1.68, p = 0.02, CAC score &gt;400 OR 1.42, p = 0.14). This association became non-significant in the highest strata of CAC score. Conclusion We found a significant association between the increasing age, male sex, diabetes and HS with the presence of CAC. HS was also associated with a more severe phenotype of CVD based on the multinomial logistic regression model. Although the association reduced for the highest strata of CAC (CAC score &gt;400) this likely reflects the overall low numbers of patients within this group and is likely a type II error. Based on these findings it may be appropriate to offer routine CVD risk stratification techniques in all those diagnosed with HS.

Institutions, entrepreneurial adaptation, and the legal form of the organization

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Indu Khurana ◽  
Dmitriy Krichevskiy ◽  
Gregory Dempster ◽  
Sean Stimpson
Keyword(s):  
Logistic Regression ◽  
Survival Rate ◽  
Regression Model ◽  
Economic Freedom ◽  
Logistic Regression Model ◽  
Legal Form ◽  
Content Type ◽  
Legal Structure ◽  
The Usa ◽  
Over Time

PurposeThis paper aims to examine how economic freedom impacts the initial choice of legal structure for startup firms. The authors do this by first exploring whether economic freedom is an essential determinant of the initial legal form of organization (LFO). The authors then explore the impact of economic freedom on firms' choice of changing their initial legal structure over time and how this change impacts their survival rate.Design/methodology/approachThe authors employ a multinomial logistic regression model to measure the initial determinants of LFO by utilizing an eight-year panel data set of 4,928 startups in the USA through the Kauffman firm survey and merge it with the Economic Freedom in North American index from the Fraser Institute. The authors then employ a logistic regression model to examine the determinants facilitating a change in legal structure over time.FindingsThe results show that economic freedom is a significant determinant in the choice of legal structure. The findings also report that the majority of startups do not change their legal form, but of those that do change the legal structure show a higher survival rate.Research limitations/implicationsMajor limitations are the size of the data and the nature of somewhat limited economic freedom differences with the USA. More nuanced measures of economic freedom would be highly desirable.Practical implicationsPolicymakers should take note that limited red tape, smoothly working labor markets and straightforward processes for changes of legal structures of organizations would improve survival and growth odds for entrepreneurs.Originality/valueDrawing on the theory of institutions, the authors attempt to bridge a gap in the literature by explicitly analyzing the determinants of the legal structure in startups in light of economic freedom. Institutional factors do not work in isolation; therefore, the authors also employ traditional entrepreneur-specific variables that affect the choice of legal structure in addition to the institutional framework.

scholarly journals Sparse estimation for case–control studies with multiple disease subtypes

Biostatistics ◽  
2020 ◽  
Author(s):  
Nadim Ballout ◽  
Cedric Garcia ◽  
Vivian Viallon
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Conditional Logistic Regression ◽  
Case Control ◽  
Case Control Studies ◽  
Conditional Logistic Regression Model ◽  
Symmetric Formulation ◽  
Disease Subtypes

Summary The analysis of case–control studies with several disease subtypes is increasingly common, e.g. in cancer epidemiology. For matched designs, a natural strategy is based on a stratified conditional logistic regression model. Then, to account for the potential homogeneity among disease subtypes, we adapt the ideas of data shared lasso, which has been recently proposed for the estimation of stratified regression models. For unmatched designs, we compare two standard methods based on $L_1$-norm penalized multinomial logistic regression. We describe formal connections between these two approaches, from which practical guidance can be derived. We show that one of these approaches, which is based on a symmetric formulation of the multinomial logistic regression model, actually reduces to a data shared lasso version of the other. Consequently, the relative performance of the two approaches critically depends on the level of homogeneity that exists among disease subtypes: more precisely, when homogeneity is moderate to high, the non-symmetric formulation with controls as the reference is not recommended. Empirical results obtained from synthetic data are presented, which confirm the benefit of properly accounting for potential homogeneity under both matched and unmatched designs, in terms of estimation and prediction accuracy, variable selection and identification of heterogeneities. We also present preliminary results from the analysis of a case–control study nested within the EPIC (European Prospective Investigation into Cancer and nutrition) cohort, where the objective is to identify metabolites associated with the occurrence of subtypes of breast cancer.

scholarly journals Determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia

2020 ◽  
Vol 12 (4) ◽  
pp. 463-476
Author(s):  
Hurgesa Hundera Hirpha ◽  
Sylvester Mpandeli ◽  
Amare Bantider
Keyword(s):  
Climate Change ◽  
Logistic Regression ◽  
Regression Model ◽  
Climate Change Adaptation ◽  
Logistic Regression Model ◽  
Smallholder Farmers ◽  
Binary Logistic Regression ◽  
Adaptation Strategies ◽  
Binary Logistic Regression Model ◽  
Content Type

Purpose The Ethiopian economy is mainly based on the rain-fed agriculture practiced by smallholder farmers. The sector is highly vulnerable to climate change impacts. This study aims to examine the determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia. Design/methodology/approach A cross-sectional survey design was used to collect quantitative data using questionnaire with 351 randomly selected smallholder farmers. To collect qualitative data focus group discussions, key informant interviews and field observations were also used. Triangulated with thematic analysis, descriptive statistics and binary logistic regression model were used for the analysis. Findings The result indicated that the majority of the smallholder farmers use at least one climate change adaptation strategy in their local areas though the strategy is generally weak. In this regard, some of the dominant climate change adaptation activities identified in the study area are using improved crop varieties, planting trees, watershed management, adjusting planting date and terracing. The result from binary logistic regression model showed that age and sex of household head, as well as their education, family size, access to agricultural extension services and training on climate change significantly influence the practices of adaptation measures. Originality/value This study would help the practitioners to modify the existing weak adaptation activities by introducing advanced and technological-based adaptation strategies to the rural farming communities.

Procurement planning as a strategic tool for public procurement effectiveness: Experience from selected public procuring entities in Dodoma city, Tanzania

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismail Abdi Changalima ◽  
Gift Onesmo Mushi ◽  
Shadrack Samwel Mwaiseje
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Public Procurement ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Content Type ◽  
Survival And Development ◽  
Procurement Planning

Purpose The significance of the public procurement function is on the survival and development of procuring entities and that of a nation at large. This study aims to focus on examining the influence of procurement planning on the effectiveness of public procurement, experience from selected public procuring entities in Dodoma city, Tanzania. Design/methodology/approach A cross-sectional design was adopted from which data were collected from 146 respondents who were purposively chosen from several public procuring entities located at Dodoma city in the United Republic of Tanzania by using a survey structured questionnaire and analysed through a binary logistic regression model. Findings Findings revealed that procurement planning as a strategic function significantly influences the effectiveness of public procurement. The binary logistic regression model included the implementation of prepared procurement plans (p = 0.039), the involvement of users as stakeholders and important institutional actors in public procurement (p = 0.033), compliance to procurement laws and regulations when planning (p = 0.016) and adequacy of budget (p = 0.042) as predictors of procurement planning were tested to be significantly related to the effectiveness of public procurement. It was concluded that public procuring entities can achieve public procurement effectiveness through procurement planning. Social implications The implications and policy recommendations of the findings of this study would be useful to procurement practitioners mostly in public procuring entities. Originality/value This study contributes to adding knowledge to the existing body of knowledge on procurement planning as an imperative activity in public procurement in Tanzania.

Factors determining child mortality in Uganda

2017 ◽  
Vol 44 (5) ◽  
pp. 633-642 ◽  
Author(s):  
Will Kaberuka ◽  
Alex Mugarura ◽  
Javan Tindyebwa ◽  
Debra S. Bishop
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Birth Weight ◽  
Regression Model ◽  
Marital Status ◽  
Birth Order ◽  
Child Mortality ◽  
Logistic Regression Model ◽  
Household Wealth ◽  
Content Type

Purpose The purpose of this paper is to establish socio-economic factors and maternal practices that determine child mortality in Uganda. Design/methodology/approach The paper examines the role of sex, birth weight, birth order and duration of breastfeeding of a child; age, marital status and education of the mother; and household wealth in determining child mortality. The study employs a logistic regression model to establish which of the factors significantly impacts child mortality in Uganda. Findings The study established that education level, age and marital status of the mother as well as household wealth significantly impact child mortality. Also important are the sex, birth weight, birth order and breastfeeding duration. Research limitations/implications Policies aimed at promoting breastfeeding and education of female children can make a significant contribution to the reduction of child mortality in Uganda. Practical implications Health care intervention programs should focus on single, poor and uneducated mothers as their children are at great risk due to poor and inadequate health care utilization. Originality/value This paper could be the first effort in examining child mortality status in Uganda using a logistic regression model.

scholarly journals Burden and predictors ofStaphylococcus aureusandS. pseudintermediusinfections among dogs presented at an academic veterinary hospital in South Africa (2007–2012)

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3198 ◽  
Author(s):  
Daniel N. Qekwana ◽  
James Wabwire Oguttu ◽  
Fortune Sithole ◽  
Agricola Odoi
Keyword(s):  
South Africa ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Multinomial Logistic Regression ◽  
Risk Of Infection ◽  
Multinomial Logistic Regression Model ◽  
Tract Infections ◽  
Veterinary Hospital ◽  
Isolated Species

BackgroundStaphylococci are commensals of the mucosal surface and skin of humans and animals, but have been implicated in infections such as otitis externa, pyoderma, urinary tract infections and post-surgical complications. Laboratory records provide useful information to help investigate these infections. Therefore, the objective of this study was to investigate the burdens of these infections and use multinomial regression to examine the associations between variousStaphylococcusinfections and demographic and temporal factors among dogs admitted to an academic veterinary hospital in South Africa.MethodsRecords of 1,497 clinical canine samples submitted to the bacteriology laboratory at a veterinary academic hospital between 2007 and 2012 were included in this study. Proportions of staphylococcal positive samples were calculated, and a multinomial logistic regression model was used to identify predictors of staphylococcal infections.ResultsTwenty-seven percent of the samples tested positive forStaphylococcusspp. The species ofStaphylococcusidentified wereS. pseudintermedius(19.0%),S. aureus(3.8%),S. epidermidis(0.7%) andS. felis(0.1%). The remaining 2.87% consisted of unspeciatedStaphylococcus. Distribution of the species by age of dog showed thatS. pseudintermediuswas the most common (25.6%) in dogs aged 2–4 years whileS. aureuswas most frequent (6.3%) in dogs aged 5–6 years.S. pseudintermedius(34.1%) andS. aureus(35.1%) were the most frequently isolated species from skin samples. The results of the multivariable multinomial logistic regression model identified specimen, year and age of the dog as significant predictors of the risk of infection withStaphylococcus. There was a significant temporal increase (RRR = 1.17; 95% CI [1.06–1.29]) in the likelihood of a dog testing positive forS. pseudintermediuscompared to testing negative. Dogs ≤ 8 years of age were significantly more likely to test positive forS. aureusthan those >8 years of age. Similarly, dogs between 2–8 years of age were significantly more likely to test positive forS. pseudintermediusthan those >8 years of age. In addition, dogs 2–4 years of age (RRR = 1.83; 1.09–3.06) were significantly more likely to test positive forS. pseudintermediuscompared to those <2 years of age. The risk of infection withS. pseudintermediusorS. aureuswas significantly higher in ear canal and skin specimens compared to other specimens.ConclusionsThe findings suggest thatS. pseudintermediusandS. aureuswere the most commonly isolated species from dogs presented at the study hospital. Age of the dog and the location of infection were significant predictors of infection with bothStaphylococcusspecies investigated. Significant increasing temporal trend was observed forS. pseudintermediusbut notS. aureus. This information is useful for guiding clinical decisions as well as future research.

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