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Dietary caffeine intake is associated with favorable metabolic profile among apparently healthy overweight and obese individuals
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Abstract<sec> <title>Background

Recent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.

Methods

In this cross-sectional study, 488 apparently healthy individuals with overweight and obesity were participated. Dietary intake was assessed by a Food Frequency Questionnaire (FFQ) and the amount of dietary caffeine was calculated. Body composition was determined by bioelectrical impedance analysis (BIA). Enzymatic methods were used to evaluate serum lipid, glucose, and insulin concentrations.

Results

Those at the highest tertile of dietary caffeine intake had lower percentage of fat mass, higher fat free mass and appetite score (P < 0.05). Also, lower total cholesterol (TC) and low density lipoprotein cholesterol (LDL-c) was observed in higher tertiles of dietary caffeine intake compared with lower tertiles. In multinomial adjusted models, those at the second tertile of dietary caffeine intake were more likely to have higher serum insulin (P = 0.04) and lower homeostatic model assessment of insulin resistance (HOMA-IR) values compared with first tertile (P = 0.03) in crude model. While, in the age, body mass index (BMI), sex, physical activity, socio-economic status (SES) and energy intake –adjusted model (Model III), those at the third tertile of dietary caffeine intake were more likely to have low serum LDL concentrations [odds ratio (OR) = 0.957; CI = 0.918–0.997; P = 0.04]. With further adjustment to dietary vegetable, fiber and grain intake, those at the third tertile of dietary caffeine intake were more likely to have low systolic blood pressure (SBP), LDL and high HDL levels compared with those at the first tertile (P < 0.05).

Conclusion

High intakes of dietary caffeine was associated with lower LDL, SBP, insulin resistance and higher HDL concentrations among overweight and obese individuals. However, due to observational design of the study, causal inference is impossible and further studies are warranted to confirm our findings.

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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Indicators Trends Of Populaion Structure Composition In Iraq And Their Relationship With Dependency Rates For The Period (1986-2010).: Indicators Trends Of Populaion Structure Composition In Iraq And Their Relationship With Dependency Rates For The Period (1986-2010).
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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EFFECT OF ANIMAL FEED SUPPLEMENTATION WITH DIFFERENT CONCENTRATIONS OF FENUGREEK SEEDS (Trigonellafoenumgraecum) ON ANIMAL PRODUCTION AND MICROBIAL CHICKEN MEAT.: EFFECT OF ANIMAL FEED SUPPLEMENTATION WITH DIFFERENT CONCENTRATIONS OF FENUGREEK SEEDS (Trigonellafoenumgraecum) ON ANIMAL PRODUCTION AND MICROBIAL CHICKEN MEAT.
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This study was conducted in the poultry field of Al-Mustansiriya University/ Baghdad, to show the effect of adding different levels 0, 1, 5 and 10% of the fenugreek seeds in the rations containing many contaminated microbes on the productive performance of broilers. 150-day-old rose meat was used with a 41 average weight (gm), were randomly allocated to 4 treatments with 3 replicates, and for each treatment 15 chicks per repetition: 0, 1, 5, and 10% (T0-T3), respectively. The results of this study showed that fenugreek seeds contain good amounts of protein, fat, ash and carbohydrates, which are 24.92, 8.82, 3.08 and 54.28 respectively. Fenugreek seeds also have high levels of tannins, coumarins and flavones, followed by saponins,

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Listening Comprehension Problems with English lectures
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The purpose of this study is to investigate learners' listening comprehension problems with Englishlectures. The study was guided by research question (What are the listening comprehension problems learners have with lectures in English).Furthermore; the main significant goal were declared through conducting this study, as well as providing some procedures of distribution the questionnaire of the study.Moreover, it presents several definitions of listening. This study definitely depends on questionnaire instrument to gathering the required data. The participants of the study were 30 learners completed their secondary school and joined at the college. Based on the findings among the five factors (text, speaker, task, environment, and list

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Publication Date
Sun Jun 06 2010
Journal Name
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Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

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Publication Date
Sun Jun 03 2012
Journal Name
Baghdad Science Journal
Copolymerization of Acrylamide with Acrylic acid
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Low conversion copolymerization of acrylamide AM (monomer-1) have been conducted with acrylic acid AA in dry benzene at 70°C , using Benzoyl peroxide BPO as initiator . The copolymer composition has been determined by elemental analysis. The monomer reactivity ratios have been calculated by the Kelen-Tudos and Finman-Ross graphical procedures. The derived reactivity ratios (r1, r2) are: (0.620, 0.996) for (AM / AA) systems , and found that the reactivity of the monomer AA is more than the monomer AM in the copolymerization of (AA/AM) system. The reactivity ratios values were used for microstructures calculation.

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Publication Date
Sat Oct 01 2022
Journal Name
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Neudesin Levels in Patients with Thyroidism
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Background: Neudesin is a peptide secreted in brain and adipose tissues that has neural and metabolic functions. Its role as regulator of energy expenditure leads to assumption that its level may be regulated depending on thyroid gland pathology. Objective: This study aimed to investigate serum neudesin levels in patients with thyroidism and to evaluate1 any possible relationship between plasma neudesin levels and thyroid hormone levels. Methods: The study included 100 women with newly diagnosed thyroidisim were subdivided into two groups: hyperthyroidism group (50 female patients with age ranged from 18 to 60 years) and hypothyroidism group (50 female patients with age ranged from 18 to 75 years). A control group (30 healthy females with a

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Publication Date
Thu Apr 23 2015
Journal Name
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Glycine Poly Acrylate with 4-Aminoantipyrine
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Transactions on Engineering and Sciences

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Wed Feb 01 2023
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Wed Jun 01 2011
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Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

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