Analysis of Diabetes Apps to Assess Privacy-Related Permissions: Systematic Search of Apps by José Javier Flors-Sidro (18518946)

“…<h3>Background</h3><p dir="ltr">Mobile health has become a major vehicle of support for people living with diabetes. Accordingly, the availability of mobile apps for diabetes has been steadily increasing. …”

Prevalence and risk factors of poor indoor air quality and sick house syndrome symptoms in Dubai by ALI, MUNA IBRAHIM

“…None covered a sample including the different nationalities living in UAE. That is important in revealing more realistic results reflecting the present IEQ and SHS in UAE housing. …”
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The effects of Social Determinants of Health on Type 2 Diabetes Outcomes (A1C) by Awad, Nathalie

“…Diabetes duration of 5-10 years increased the odds of having uncontrolled A1C by more than 3 folds. …”
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Early feeding practices and associated factors in Sudan: a cross-sectional analysis from multiple Indicator cluster survey by Manar E. Abdel-Rahman (5593553)

“…The sample includes women who had a live birth in the two years before the survey and their self-report on early breastfeeding practices, namely early initiation and prelacteal feeding. …”

Predictors of malnutrition among older residents in Qatari long-term care facilities: a retrospective study by Al Anoud Ali H. Z. AlFehaidi (21633416)

“…<h3>Background</h3><p dir="ltr">Malnutrition is a prevalent issue among older adults in long-term care facilities and is associated with adverse health outcomes and increased healthcare costs. Identifying the predictors of malnutrition in this population is crucial for developing effective intervention strategies. …”

Effect of Intravenous Mannitol on Intraocular Pressure Changes in Vitrectomized and Non-Vitrectomized Eyes: A Systematic Review and Meta-Analysis by HASHEM ABU SERHAN (19737499)

“…In vitrectomized eyes, notable decreases were observed: at 30 min, the Ratio of Means (ROM) was 0.81 (95% CI: 0.53; 1.24), indicating a 19% reduction; at 60 min, the ROM of 0.833 (95% CI: 0.77; 0.89) showed a 16.7% reduction; at 90 min, the ROM of 0.757 (95% CI: 0.755; 0.758) corresponded to a 24.3% reduction; at 2 h, the ROM of 0.726 (95% CI: 0.642; 0.820) reflected a 27.4% reduction; at 3 h, the ROM of 0.692 (95% CI: 0.600; 0.797) resulted in a 30.8% reduction; and at 4 h, the ROM of 0.700 (95% CI: 0.363; 1.350) indicated a 30% reduction. …”

Global, regional, and national burden of respiratory tract cancers and associated risk factors from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019 by Hedyeh Ebrahimi (7321358)

“…From 2010 to 2019, the number of new tracheal, bronchus, and lung cancer cases increased by 23·3% (12·9 to 33·6) globally and the number of larynx cancer cases increased by 24·7% (16·0 to 34·1) globally. …”

Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019 by Gregory A. Roth (6302315)

“…The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. …”

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021 by Kanyin Liane, Ong

“…However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. …”
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The English Language Centre Community College Qatar: A Position Report by Irum Naz (17948078)

“…The idea of integrating skills was also put forth as a means of increasing the efficiency of the program and rendering it more cost effective. …”

Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 by Christopher J L Murray (13580635)

“…Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. …”