Social determinants of health (SDH) profoundly influence diabetes outcomes; nevertheless, their impact on the Iraqi diabetic population remains under researched. The objectives of this study were To investigate the relationship between particular social determinants of health (SDH) variables namely food and housing insecurity, social support, income, and education and clinical outcomes, including HbA1c levels, medication adherence, and patient satisfaction among Iraqi diabetic patients. A cross-sectional study involving 212 diabetic patients in Iraq was conducted. Participants attending a healthcare facility in Iraq filled out validated questionnaires regarding social determinants of health, medication adherence, and satisfaction. HbA1c readings were extracted from medical records. Data were examined utilizing Spearman’s correlation. The average HbA1c was 7.4% ± 2.7. A majority of individuals had moderate housing insecurity (79.2%) and low food insecurity (75%). The principal discovery was that no social determinants of health variables exhibited a significant connection with HbA1c levels. Patient satisfaction exhibited a positive correlation with social support (p < 0.001) and higher income (p = 0.023), while demonstrating a negative correlation with housing insecurity (p = 0.040). Social support was the sole factor substantially correlated with improved medication adherence (p = 0.003). In conclusion, SDH were not directly associated with diabetes control but significantly influenced patient-reported experiences. Social assistance and money increased contentment, whereas housing insecurity diminished it. Social support was a significant factor in drug adherence. The results underscore the necessity of addressing psychosocial and economic issues to enhance the quality of diabetes care in Iraq.
Quantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee
... Show MoreA new class of biologically active nanocomposites and modified polymers based on poly (vinyl alcohol) (PVA) with some organic compounds [II, IV, V and VI] were synthesized using silver nanoparticles (Ag-NPs). All compounds were synthesized using nucleophilic substitution interactions and characterized by FTIR, DSC and TGA. The biological activity of the modified polymers was evaluated against: gram (+) (staphylococcus aureus) and gram (-): (Es cherichia coli bacteria). Antimicrobial films are developed based on modified poly (vinyl alcohol) MPVA and Ag-NPs nanoparticles. The nanocomposites and modified polymers showed better antibacterial activities against Escherichia coli (Gram negative) than against Staphyloc
... Show More4-aminobenzenesulfonamide conjugates of ibuprofen (compound 10) and indomethacin (compound 11) have been designed and synthesized by the reaction of sulfanilamide (compound 7) with 2-(4-isobutylphenyl) propanoic acid (ibuprofen) and 2-(1-(4-chlorobenzoyl)-5-methoxy-2-methyl-1H-indol-3-yl)acetic acid (indomethacin) for the evaluation as potential anti-inflammatory agents with expected selectivity against COX-2 enzyme. In vivo acute anti-inflammatory activity of the synthesized final compounds (10 and 11) was evaluated in rats using egg-white induced edema model of inflammation in a dose equivalent to (10mg/Kg) of ibuprofen and (2mg/kg) of indomethacin. The tested compounds pr
... Show MoreNew twin compounds having four-, five-, and seven- membered heterocyclic rings were synthesized via Schiff bases (1a,b) which were obtained by the condensation of o-tolidine with two moles of 4- N,N-dimethyl benzaldehyde or 4- chloro benzaldehyde. The reaction of these Schiff bases with two moles of phenyl isothiocyanate, phenyl isocyanate or naphthyl isocyanate as in scheme(1) led to the formation of bis -1,3- diazetidin- 2- thion and bis -1,3- diazetidin -2-one derivatives (2-4 a,b). While in scheme (2) bis imidazolidin-4-one (5a,b) ,bistetrazole (6a,b) and bis thiazolidin-4-one (7a,b) derivatives were produced by reacting the mentioned Schiff bases(1a,b)with two moles of glycine, sodium azide or thioglycolic acid, respectively. The new b
... Show More<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c
... Show MoreThree scolopacids out of 150 are found infected with Haemoproteus scolopaci Galli-
Valerio 1929 and H. tringae n. sp. A detailed description of the new taxon is presented along
with a comparison of the diagnostic measurements between the two species.
Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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