Search

Objective - Studies indicate an inverse association between sleep duration and psychological distress. We aimed to explore associations between changes in sleep duration and changes in psychological distress in girls and boys. Methods - The Fit Futures Study is a broad adolescent study providing data from 373 girls and 294 boys aged 15–18 years collected in 2010/2011 (FF1) and 2012/2013 (FF2). Psychological distress was measured by the Hopkins Symptom Checklist (HSCL-10) and sleep duration was self-reported. Change score variables were calculated as the change between baseline and follow-up for sleep duration and HSCL-10, respectively. Associations between changes in sleep duration and changes in HSCL-10 were explored by linear regressions, in gender-stratified analyses. Results - At FF1, girls and boys slept on average 6.93 (SD = 1.08) and 7.05 (SD = 1.20) hours per night respectively, and correspondingly, 6.83 (SD = 1.19) and 6.85 (SD = 1.21) at FF2. At FF1, 22.8% of the girls and 25.8% of the boys slept ≤ 6 h per night, and correspondingly 28.0% and 28.2% at FF2. In girls and boys, one unit increase (30 min) in sleep duration was associated with a decrease in HSCL-10 score of B [95% CI] = −0.090 [−0.131, −0.048], p Conclusion - Our findings show that increased sleep duration was associated with decreased psychological distress during adolescence. Future studies should examine the causality between sleep duration and psychological distress.

Correction to Lancet Gastroenterol Hepatol 2022; 7: 627-47. Lancet Gastroenterol Hepatol. 2022 Aug;7(8):704. doi: 10.1016/S2468-1253(22)00210-2. PMID: 35809605. Background: Colorectal cancer is the third leading cause of cancer deaths worldwide. Given the recent increasing trends in colorectal cancer incidence globally, up-to-date information on the colorectal cancer burden could guide screening, early detection, and treatment strategies, and help effectively allocate resources. We examined the temporal patterns of the global, regional, and national burden of colorectal cancer and its risk factors in 204 countries and territories across the past three decades. Methods: Estimates of incidence, mortality, and disability-adjusted life years (DALYs) for colorectal cancer were generated as a part of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019 by age, sex, and geographical location for the period 1990-2019. Mortality estimates were produced using the cause of death ensemble model. We also calculated DALYs attributable to risk factors that had evidence of causation with colorectal cancer. Findings: Globally, between 1990 and 2019, colorectal cancer incident cases more than doubled, from 842 098 (95% uncertainty interval [UI] 810 408-868 574) to 2·17 million (2·00-2·34), and deaths increased from 518 126 (493 682-537 877) to 1·09 million (1·02-1·15). The global age-standardised incidence rate increased from 22·2 (95% UI 21·3-23·0) per 100 000 to 26·7 (24·6-28·9) per 100 000, whereas the age-standardised mortality rate decreased from 14·3 (13·5-14·9) per 100 000 to 13·7 (12·6-14·5) per 100 000 and the age-standardised DALY rate decreased from 308·5 (294·7-320·7) per 100 000 to 295·5 (275·2-313·0) per 100 000 from 1990 through 2019. Taiwan (province of China; 62·0 [48·9-80·0] per 100 000), Monaco (60·7 [48·5-73·6] per 100 000), and Andorra (56·6 [42·8-71·9] per 100 000) had the highest age-standardised incidence rates, while Greenland (31·4 [26·0-37·1] per 100 000), Brunei (30·3 [26·6-34·1] per 100 000), and Hungary (28·6 [23·6-34·0] per 100 000) had the highest age-standardised mortality rates. From 1990 through 2019, a substantial rise in incidence rates was observed in younger adults (age

Purpose: This study aimed at evaluating the diagnostic performance of standard greyscale and inverted greyscale Chest X-ray (CXR) using Computed Tomography (CT) scan as a gold standard. Methods: In this retrospective study, electronic medical records of 120 patients who had valid CXR and High-resolution CT (HRCT) within less than 24 hours after having a positive COVID-19 RT-PCR test during the period from May 19th to May 23rd, 2020, in a single tertiary care center were reviewed. PA chest radiographs were presented on 2 occasions to 5 radiologists to evaluate the role and appropriateness of standard greyscale and inverted greyscale chest radiographs (CXR) when images are viewed on high-specification viewing systems using a primary display monitor and compared to computed tomography (CT) findings for screening and management of suspected or confirmed COVID-19 patients. Results: Ninety-six (80%) patients had positive CT findings, 81 (67.5%) had positive grey scale CXR lesions, and 25 (20.8%) had better detection in the inverted grey scale CXR. The CXR sensitivity for COVID-19 pneumonia was 93.8% (95% CI (86.2% - 98.0%) and the specificity was 48.7% (95% CI (32.4% - 65.2%). The CXR sensitivity of detecting lung lesions was slightly higher in male (95.1% (95% CI (86.3% - 99.0%)) than female (90.0% (95% CI (68.3% - 98.8%)), while the specificity was 48.0% (95% CI (27.8% - 68.7%) and 50.0% (95% CI (23.0% - 77.0%) in males and females, respectively. However, no significant difference was detected in ROC area between men and women. Conclusion: The sensitivity of detecting lung lesions of CXR was relatively high, particularly in men. The results of the study support the idea of considering conventional radiographs as an important diagnostic tool in suspected COVID-19 patients, especially in healthcare facilities where there is no access to HRCT scans. CXR shows high sensitivity for detecting lung lesions in HRCT confirmed COVID-19 patients. Better detection of lesions was noted in the inverted greyscale CXR in 20.8% of cases, with positive findings in standard greyscale CXR. Conventional radiographs can be used as diagnostic tools in suspected COVID-19 patients, especially in healthcare facilities where there is no access to HRCT scans.

Objectives: To investigate the impact of COVID-19 vaccines in the United Arab Emirates (UAE) on the trend of COVID-19-related hospitalization, intensive care unit (ICU) admissions, and case fatality rate (CFR), this retrospective chart review was conducted. background: Real-world evidence from the Middle East about the effectiveness of COVID-19 vaccination is still lacking. Methods: We included patients admitted to two tertiary hospitals from October 2020 to July 2022. Patients were categorized into non-vaccinated, partially-vaccinated, and fully-vaccinated groups. objective: To investigate the impact of COVID-19 vaccines in the United Arab Emirates (UAE) on the trend of COVID-19-related hospitalization, intensive care unit (ICU) admissions, and case fatality rate (CFR), this retrospective chart review was conducted. Results: A total of 2277 cases were included, with 27.49% being non-vaccinated. The monthly trend of admitted patients dropped from 1264 (56.50%) cases in the first half of 2021 to 194 (8.67%) cases in the first half of 2022, with a reduction rate of 84.65%. The trend of ICU admission followed the overall hospital admission rate, with an overall CFR of 0.88%, 95% CI (0.54% to 1.35%), and a virulence rate of 1.76%, 95% CI (1.26% to 2.38%). The incidence of ICU admission in the unvaccinated group was 4.79%, compared to 0% and 0.97% in the partially-vaccinated and fully-vaccinated groups, respectively (p Conclusion: Among the study population, COVID-19 vaccines showed promising efficacy in reducing the trend of COVID-19-related hospitalization, ICU admission, and mortality. Full vaccination might reduce the burden of COVID-19 on healthcare. result: A total of 2277 cases were included, with 27.49 other: None

Background Cardiovascular disease (CVD) is the leading cause of death in the world. In the United Arab Emirates (UAE), it accounts for 40% of mortality. CVD is caused by multiple cardiometabolic risk factors (CRFs) including obesity, dysglycemia, dyslipidemia, hypertension and central obesity. However, there are limited studies focusing on the CVD risk burden among young Emirati adults. This study investigates the burden of CRFs in a sample of young Emiratis, and estimates the distribution in relation to sociodemographic and behavioral determinants. Methods Data was used from the baseline data of the UAE Healthy Future Study volunteers. The study participants were aged 18 to 40 years. The study analysis was based on self-reported questionnaires, anthropometric and blood pressure measurements, as well as blood analysis. Results A total of 5167 participants were included in the analysis; 62% were males and the mean age of the sample was 25.7 years. The age-adjusted prevalence was 26.5% for obesity, 11.7% for dysglycemia, 62.7% for dyslipidemia, 22.4% for hypertension and 22.5% for central obesity. The CRFs were distributed differently when compared within social and behavioral groups. For example, obesity, dyslipidemia and central obesity in men were found higher among smokers than non-smokers (p Conclusions CRFs are highly prevalent in the young Emirati adults of the UAE Healthy Future Study. The difference in CRF distribution among social and behavioral groups can be taken into account to target group-specific prevention measures.

This study describes the primary and secondary infertility in patients attending fertility clinics and reports factors associated with primary infertility. A cross-sectional survey was conducted in two fertility clinics in Abu Dhabi Emirate, United Arab Emirates (UAE) between December 2020 and May 2021. The collected information covered sociodemographic, lifestyle, medical, and fertility-related characteristics. The mean age and age at marriage (±SD) of the 928 patients were 35.7 (±6.7) and 25.2 (±6.3) years, respectively. Of the total, 72.0% were obese and overweight, 26.6% reported a consanguineous marriage, and 12.5% were smokers. Secondary infertility (62.5%) was more frequent than primary infertility (37.5%). Primary infertility was inversely associated with age (aOR, 0.94, 95% CI: 0.91–0.98) and not being overweight (aOR, 0.6, 95% CI: 0.4–0.9) while positively associated with a nationality other than Middle Eastern nationality (aOR, 1.9, 95% CI: 1.1–3.3), married for ≤5 years (aOR, 6.0, 95% CI: 3.9–9.3), in a nonconsanguineous marriage (aOR, 2.4, 95% CI: 1.5–3.9), having a respiratory disease (aOR, 2.3, 95% CI: 1.1–4.6), an increased age at puberty (aOR, 1.2, 95% CI: 1.0–1.3), and self-reported 6&ndash

Low Birth weight (LBW) infants pose a serious public health concern worldwide in both the short and long term for infants and their mothers. Infant weight prediction prior to birth can help to identify risk factors and reduce the risk of infant morbidity and mortality. Although many Machine Learning (ML) algorithms have been proposed for LBW prediction using maternal features and produced considerable model performance, their performance needs to be improved so that they can be adapted in real-world clinical settings. Existing algorithms used for LBW classification often fail to capture structural information from the tabular dataset of patients with different complications. Therefore, to improve the LBW classification performance, we propose a solution by transforming the tabular data into a knowledge graph with the aim that patients from the same class (normal or LBW) exhibit similar patterns in the graphs. To achieve this, several features related to each node are extracted such as node embedding using node2vec algorithm, node degree, node similarity, nearest neighbors, etc. Our method is evaluated on a real-life dataset obtained from a large cohort study in the United Arab Emirates which contains data from 3453 patients. Multiple experiments were performed using the seven most commonly used ML models on the original dataset, graph features, and a combination of features, respectively. Experimental results show that our proposed method achieved the best performance with an area under the curve of 0.834 which is over 6% improvement compared to using the original risk factors without transforming them into knowledge graphs. Furthermore, we provide the clinical relevance of the proposed model that are important for the model to be adapted in clinical settings.

IntroductionThe induction and speed of production of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) immune biomarkers may vary by type and number of inoculated vaccine doses. This study aimed to explore variations in SARS-CoV-2 anti-spike (anti-S), anti-nucleocapsid (anti-N), and neutralizing immunoglobulin G (IgG) antibodies, and T-cell response by type and number of SARS-CoV-2 vaccine doses received.MethodsIn a naturally exposed and SARS-CoV-2–vaccinated population, we quantified the anti-S, anti-N, and neutralizing IgG antibody concentration and assessed T-cell response. Data on socio-demographics, medical history, and history of SARS-CoV-2 infection and vaccination were collected. Furthermore, nasal swabs were collected to test for SARS-CoV-2 infection. Confounder-adjusted association between having equal or more than a median concentration of the three IgG antibodies and T-cell response by number and type of the inoculated vaccines was quantified.ResultsWe surveyed 952 male participants with a mean age of 35.5 years ± 8.4 standard deviations. Of them, 52.6% were overweight/obese, and 11.7% had at least one chronic comorbidity. Of the participants, 1.4, 0.9, 20.2, 75.2, and 2.2% were never vaccinated, primed with only one dose, primed with two doses, boosted with only one dose, and boosted with two doses, respectively. All were polymerase chain reaction-negative to SARS-CoV-2. BBIBP-CorV (Sinopharm) was the most commonly used vaccine (92.1%), followed by rAd26-S + rAd5-S (Sputnik V Gam-COVID-Vac) (1.5%) and BNT162b2 (Pfizer-BioNTech) (0.3%). Seropositivity to anti-S, anti-N, and neutralizing IgG antibodies was detected in 99.7, 99.9, and 99.3% of the study participants, respectively. The T-cell response was detected in 38.2% of 925 study participants. Every additional vaccine dose was significantly associated with increased odds of having ≥median concentration of anti-S [adjusted odds ratio (aOR), 1.34; 95% confidence interval (CI): 1.02–1.76], anti-N (aOR, 1.35; 95% CI: 1.03–1.75), neutralizing IgG antibodies (aOR, 1.29; 95% CI: 1.00–1.66), and a T-cell response (aOR, 1.48; 95% CI: 1.12–1.95). Compared with boosting with only one dose, boosting with two doses was significantly associated with increased odds of having ≥median concentration of anti-S (aOR, 13.8; 95% CI: 1.78–106.5), neutralizing IgG antibodies (aOR, 13.2; 95% CI: 1.71–101.9), and T-cell response (aOR, 7.22; 95% CI: 1.99–26.5) although not with anti-N (aOR, 0.41; 95% CI: 0.16–1.08). Compared with priming and subsequently boosting with BBIBP-CorV, all participants who were primed with BBIBP-CorV and subsequently boosted with BNT162b2 had ≥median concentration of anti-S and neutralizing IgG antibodies and 14.6-time increased odds of having a T-cell response (aOR, 14.63; 95% CI: 1.78–120.5). Compared with priming with two doses, boosting with the third dose was not associated, whereas boosting with two doses was significantly associated with having ≥median concentration of anti-S (aOR, 14.20; 95% CI: 1.85–109.4), neutralizing IgG (aOR, 13.6; 95% CI: 1.77–104.3), and T-cell response (aOR, 7.62; 95% CI: 2.09–27.8).ConclusionAchieving and maintaining a high blood concentration of protective immune biomarkers that predict vaccine effectiveness is very critical to limit transmission and contain outbreaks. In this study, boosting with only one dose or with only BBIBP-CorV after priming with BBIBP-CorV was insufficient, whereas boosting with two doses, particularly boosting with the mRNA-based vaccine, was shown to be associated with having a high concentration of anti-S, anti-N, and neutralizing IgG antibodies and producing an efficient T-cell response.

BackgroundFor more than half a century, there has been much research and controversies on how to accurately screen for and diagnose gestational diabetes mellitus (GDM). There is a paucity of updated research among the Emirati population in the United Arab Emirates (UAE). The lack of a uniform GDM diagnostic criteria results in the inability to accurately combine or compare the disease burden worldwide and locally. This study aimed to compare the incidence of GDM in the Emirati population using six diagnostic criteria for GDM.MethodsThe Mutaba’ah study is the largest multi-center mother and child cohort study in the UAE with an 18-year follow-up. We included singleton pregnancies from the Mutaba’ah cohort screened with the oral glucose tolerance test (OGTT) at 24–32 weeks from May 2017 to March 2021. We excluded patients with known diabetes and with newly diagnosed diabetes. GDM cumulative incidence was determined using the six specified criteria. GDM risk factors were compared using chi-square and t-tests. Agreements among the six criteria were assessed using kappa statistics.ResultsA total of 2,546 women were included with a mean age of 30.5 ± 6.0 years. Mean gravidity was 3.5 ± 2.1, and mean body mass index (BMI) at booking was 27.7 ± 5.6 kg/m2. GDM incidence as diagnosed by any of the six criteria collectively was 27.1%. It ranged from 8.4% according to the EASD 1996 criteria to 21.5% according to the NICE 2015 criteria. The two most inclusive criteria were the NICE 2015 and the IADPSG criteria with GDM incidence rates of 21.5% (95% CI: 19.9, 23.1) and 21.3% (95% CI: 19.8, 23.0), respectively. Agreement between the two criteria was moderate (k = 0.66; p < 0.001). The least inclusive was the EASD 1996 criteria [8.4% (95% CI: 7.3, 9.6)]. The locally recommended IADPSG/WHO 2013 criteria had weak to moderate agreement with the other criteria, with Cohen’s kappa coefficient ranging from (k = 0.51; p < 0.001) to (k = 0.71; p < 0.001). Most of the GDM risk factors assessed were significantly higher among those with GDM (p < 0.005) identified by all criteria.ConclusionsThe findings indicate discrepancies among the diagnostic criteria in identifying GDM cases. This emphasizes the need to unify GDM diagnostic criteria in this population to provide accurate and reliable incidence estimates for healthcare planning, especially because the agreement with the recommended criteria was not optimal.

BackgroundHerpes simplex virus type 2 (HSV-2) is a common genitally-transmitted viral infection affecting more than 400 million individuals globally. In the United Arab Emirates (UAE), in specific at-risk population groups, the burden of HSV-2 has not been reported. This study investigated the prevalence of HSV-2 IgG antibodies in patients seeking fertility treatment and characterized patients with seropositivity to HSV-2 IgG antibodies.MethodologyA cross-sectional sample of patients seeking fertility treatment in a major fertility clinic in Abu Dhabi, UAE was surveyed from April to May 2021. Patients were consecutively invited to complete self-administered questionnaires and provide blood for HSV-2 testing. Information on sociodemographics, medical history, and infertility was collected. Serum specimens were screened using an enzyme-linked immunosorbent assay for HSV-2 IgG antibodies detection.ResultsTwo hundred and ninety-nine patients were surveyed and provided blood samples. The mean age of the patients was 35.9 ± 6.8 [mean ± standard deviation (SD)] years with 89.3% being women. Sixty-six percent were overweight or obese, 25.0% had at least one chronic comorbidity, and 19.6% reported ever-had genital infection. More than two-thirds (68.3%) of the patients were infertile for ≥ 6 months. Of the 42 infertile males, 69.0% had an abnormal semen analysis. HSV-2 IgG antibodies was detected in 12.4% of patients. The HSV-2 IgG seropositive patients had a higher mean age (39.5 vs. 35.4 years; p < 0.001) compared to seronegative patients. HSV-2 IgG antibodies seropositivity was more common in males (15.6%) than females (12.0%), in patients with secondary (14.1%) vs. primary (9.2%) infertility, or in males with abnormal (10.3%) vs. normal (7.7%) semen.ConclusionExposure to HSV-2 at any time in patients seeking fertility treatment in the UAE was found to be slightly common in more than one out of 10 patients. Tailored health campaigns on HSV-2 prevention are warranted.

Peer reviewed: True, INTRODUCTION: Metabolic syndrome (MetS) is a multiplex of risk factors that predispose people to the development of diabetes and cardiovascular disease (CVD), two of the major non-communicable diseases that contribute to mortality in the United Arab Emirates (UAE). MetS guidelines require the testing of fasting samples, but there are evidence-based suggestions that non-fasting samples are also reliable for CVD-related screening measures. In this study, we aimed to estimate MetS and its components in a sample of young Emiratis using HbA1c as another glycemic marker. We also aimed to estimate the associations of some known CVD risk factors with MetS in our population. METHODS: The study was based on a cross-sectional analysis of baseline data of 5161 participants from the UAE Healthy Future Study (UAEHFS). MetS was identified using the NCEP ATP III criteria, with the addition of HbA1c as another glycemic indicator. Fasting blood glucose (FBG) and HbA1c were used either individually or combined to identify the glycemic component of MetS, based on the fasting status. Multivariate regression analysis was used to test for associations of selected social and behavioral factors with MetS. RESULTS: Our sample included 3196 men and 1965 women below the age of 40 years. Only about 21% of the sample were fasting at the time of recruitment. The age-adjusted prevalence of MetS was estimated as 22.7% in males and 12.5% in females. MetS prevalence was not statistically different after substituting FBG by HbA1c in the fasting groups (p > 0.05). Age, increased body mass index (BMI), and family history of any metabolic abnormality and/or heart disease were consistently strongly associated with MetS. CONCLUSION: MetS is highly prevalent in our sample of young Emirati adults. Our data showed that HbA1c may be an acceptable tool to test for the glycemic component of MetS in non-fasting samples. We found that the most relevant risk factors for predicting the prevalence of MetS were age, BMI, and family history.

Objective We aim to investigate high-resolution CT features of COVID-19 infection in Abu Dhabi, UAE, and to compare the diagnostic performance of CT scan with RT-PCR test. Methods Data of consecutive patients who were suspected to have COVID-19 infection and presented to our hospital were collected from March 2, 2020, until April 12, 2020. All patients underwent RT-PCR test; out of which 53.8% had chest CT scan done. Using RT-PCR as a standard reference, the sensitivity and specificity of the CT scan were calculated. We also analyzed the most common imaging findings in patients with positive RT-PCR results. Results The typical HRCT findings were seen in 50 scans (65.8%) out of total positive ones; 44 (77.2%) with positive RT-PCR results and 6 (31.6%) with negative results. The peripheral disease distribution was seen in 86%, multilobe involvement in 70%, bilateral in 82%, and posterior in 82% of the 50 scans. The ground glass opacities were seen in 50/74 (89.3%) of the positive RT-PCR group. The recognized GGO patterns in these scans were: rounded 50%, linear 38%, and crazy-paving 24%. Using RT-PCR as a standard of reference, chest HRCT scan revealed a sensitivity of 68.8% and specificity of 70%. Conclusion The commonest HRCT findings in patients with COVID-19 pneumonia were peripheral, posterior, bilateral, multilobe rounded ground-glass opacities. The performance of HRCT scan can vary depending on multiple factors.

Pharmacogenomics (PGx) education is crucial to support the effective delivery of PGx services in any health care system. We mapped the current educational environment of genomics and PGx in the United Arab Emirates (UAE) and assessed the readiness of the accredited higher education system to move forward with the implementation of PGx in the country. We employed a mixed-methods triangulated approach to map the PGx educational environment in UAE. We used two qualitative methods and one quantitative method. University curricula inspection, interviews, and questionnaires were the main resources of data. PGx was taught in 6 out of 21 accredited universities, but only for pharmacy majors. Only three out of six PGx courses were stand-alone. Majority of academia exhibited positive attitudes toward the availability and accessibility of genetic testing, with 89% agreeing that the government should invest more money into its development. Interviews with academics and, importantly, the commissioners who oversee the accreditation process of universities in UAE revealed recurrent themes that included recognizing the importance of genomic medicine and PGx and called for translational and implementational research, including recruitment of experts in the field. We recommend, as supported by our findings in this study, the creation of standardized curriculum of genomics and PGx for each health science field, using the blended teaching approach, and benchmarking internationally accredited universities to foster international collaboration and improve the education and practice of genomics in the clinic and public health systems. An 11-item genomics and PGx strategy is presented herein. Finally, the mixed-methods study design employed in this research may also serve as a model conceptual frame for other science education mapping efforts at country or multi-institutional scales in the future.

Background and Aim: Mapping the power, interest, and stance of stakeholders is a cornerstone for genomic medicine implementation. In this study, we aimed at mapping the power/interest of various stakeholders in United Arab Emirates (UAE) and exploring their attitudes toward pressing health genomics aspects. The overarching aim of this study is to facilitate the construction of a road map for the full implementation of genomic medicine and pharmacogenomics in the UAE with potential applicability to many healthcare systems around the world. Methods: A qualitative approach using in-depth interview was employed. Heterogeneous stakeholders were identified by experts in the field. The analysis of the data was a hybrid of deductive and inductive approach using NVivo software for coding and analysis. Results: 13 interviews were conducted. Following mapping the Mendelow’s matrix, we categorized the stakeholders in UAE to promoter, latent, defender, and apathetic. Most of the interviewed stakeholders emphasized the clinical demand for genomic medicine in UAE. However, many of them were less inclined to articulate the need for pharmacogenomics at the moment. The majority of stakeholders in UAE were in favor of building infrastructure for better genetic services in the country. Stakeholder from an insurance sector had contradicting stance about the cost-effectiveness of genomic medicine; the majority were concerned with the legal and ethical aspects of genomic medicine and had an opposing stance on direct-to-consumer kits. Conclusions: Implementing the Mendelow’s model will allow the systematic strategy for implementing genomic medicine in UAE. This can be achieved by engaging the key players (promoters and defenders) as well as engaging and satisfying the latent stakeholder.

Purpose To estimate the prevalence of recurrent miscarriage (RM) and investigate the association between RM and adverse maternal outcomes in subsequent pregnancies. Participants and Methods This is an interim analysis of a prospective study of 1737 pregnant women with gravidity of two or more prior to the current pregnancy. These women joined the Mutaba'ah Study between May 2017 and April 2019 and were followed up until they delivered. Hospital medical records were used to extract data on past pregnancy history and the progress and outcomes of the current pregnancy, such as gestational diabetes, preeclampsia, mode of delivery, preterm delivery, and complications at birth. Results Amongst pregnant women with at least two previous pregnancies (n=1737), there were 234 (13.5%) women with a history of two or more consecutive miscarriages. Women with RM were slightly older, more parous, and more likely to have had previous infertility treatment (all p-values

Background: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods: The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings: Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01-4·94) deaths and 105 million (95·0-116) DALYs for both sexes combined, representing 44·4% (41·3-48·4) of all cancer deaths and 42·0% (39·1-45·6) of all DALYs. There were 2·88 million (2·60-3·18) risk-attributable cancer deaths in males (50·6% [47·8-54·1] of all male cancer deaths) and 1·58 million (1·36-1·84) risk-attributable cancer deaths in females (36·3% [32·5-41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6-28·4) and DALYs by 16·8% (8·8-25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9-42·8] and 33·3% [25·8-42·0]). Interpretation: The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. We are grateful to the surveillance systems, including cancer registries, that generated and shared observed cancer burden data. S M Aljunid acknowledges the Department of Health Policy and Management, College of Public Health, Kuwait University for the approval and support to participate in this research project. H Ariffin acknowledges support from the Ministry of Higher Education, Malaysia (grant FRGS/1/2021/SKK0/UM/01/1). F Barra acknowledges support from Lega Italiana per la Lotta contro i Tumori - LILT - Bando 5 x 1000 anno 2019. L Belo and M Carvalho acknowledge the support from FCT in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of UCIBIO and the project LA/P/0140/2020 of i4HB. A J Cohen was supported by the Health Effects Institute, Boston, MA, USA. J Conde acknowledges financial support from the European Research Council - ERC Starting Grant 848325. V M Costa acknowledges her grant (SFRH/BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006. T C Ekundayo was supported by the African-German Network of Excellence in Science (AGNES), the Federal Ministry of Education and Research (BMBF) and the Alexander von Humboldt Foundation (AvH). N Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). J C Glasbey is support by a Doctoral Research Fellowship from the National Institute of Health Research (NIHR300175). V K Gupta and V B Gupta acknowledge funding support from National Health and Medical Research Council (NHMRC), Australia. C Herteliu, A Pana, and M Ausloos acknowledge partial support by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. C Herteliu is also partially supported by a grant of the Romanian Ministry of Research Innovation and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021. S Hussain was supported from Operational Programme Research, Development and Education–Project, Postdoc2MUNI (number CZ.02.2. 69/0.0/0.0/18_053/0016952). M Jakovljevic acknowledges partial support through the grant OI 175 014 of the Ministry of Education Science and Technological Development of the Republic of Serbia. J H Kauppila acknowledges research grants from Sigrid Jusélius Foundation and the Finnish Cancer Foundation. M N Khatib acknowledges support from Datta Meghe Institute of Medical Sciences (deemed-to-be-university). Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia [XMUMRF/2020-C6/ITCM/0004]. S L Koulmane Laxminarayana acknowledges institutional assistance by Manipal Academy of Higher Education, Manipal. K Krishan is supported by the UGC Centre of Advanced Study (Phase II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. I Landires is a member of the Sistema Nacional de Investigación (SNI), which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). M-C Li was supported by the Ministry of Science and Technology, Taiwan (MOST 110-2314-B-003-001). G Liu acknowledges support from the CREATE Hope scientific fellowship from Lung Foundation Australia. J Liu acknowledges support from the National Natural Science Foundation (72122001). J A Loureiro was supported by Scientific Employment Stimulus (FCT; CEECINST/00049/2018). E Mathews is supported by a Clinical and Public Health Early Career Fellowship (grant number IA/CPHE/17/1/503345) from the DBT India Alliance/Wellcome Trust Department of Biotechnology, India Alliance (2018–2023). T J Meretoja was supported by an unrestricted grant from Cancer Foundation Finland sr. S Mohammed acknowledges a fellowship grant from Alexander von Humboldt Foundation, outside the submitted work. M Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. L Monasta received support from the Italian Ministry of Health at the Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste - Italy (RC 34/2017). U Mons is supported by the Marga and Walter Boll Foundation, Kerpen, Germany. M A Moosavi acknowledges the financial support of National Institute of Genetics Engineering and Biotechnology (NIGEB). J Musa acknowledges support from the NIH/FICK43TW011416 for research-protected time for cervical cancer research and career development at University of Jos. V Nuñez-Samudio is a member of the Sistema Nacional de Investigación (SNI), which is supported by Panama’s Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT). O O Odukoya acknowledges support by the Fogarty International Center of the National Institutes of Health under the award number K43TW010704 for research-protected time. The content is solely the responsibility of all the authors and does not necessarily represent the official views of the National Institutes of Health. A S Oguntade acknowledges funding by a doctoral scholarship from the Nuffield Department of Population Health, University of Oxford (Oxford Population Health). J R Padubidri acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for their constant support in research collaborations. R G Pestell acknowledges support from NIH grant W81XWH1810605 Breast Cancer Research, Breakthrough Grant R21 CA235139-01. Z Z Piracha acknowledges the International Center of Medical Sciences Research (ICMSR), Islamabad (44000), Pakistan. R A Radhakrishnan acknowledges support from Wellcome Trust/DBT India Alliance - IA/CPHI/18/1/503927. U Saeed acknowledges the International Center of Medical Sciences Research (ICMSR), Islamabad, Pakistan. A M Samy acknowledges the support from Ain Shams University and the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Science and Technology Program (grant number KQTD20190929172835662). H R Shahsavari acknowledges the Institute for Advanced Studies in Basic Sciences (IASBS) Research Council. A Shetty acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. D A S Silva acknowledges financing in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001 and D A S Silva is supported in part by CNPq-Brazil (309589/2021-5). L M L R Silva was supported by project CENTRO-04-3559-FSE-000162, Fundo Social Europeu (FSE). Am Singh is supported by the International Graduate Research Scholarship, University of Tasmania. R Suliankatchi Abdulkader acknowledges support from ICMR—National Institute of Epidemiology. B Unnikrishnan acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal. H Xiao acknowledges support from the Public Health Sciences Division of the Fred Hutchinson Cancer Research Center. X Xu is supported by the University of New South Wales (Australia) Scientia Program. C Yu was supported by the National Natural Science Foundation of China (grant number 82173626) and Wuhan Medical Research Program of Joint Fund of Hubei Health Committee (grant number WJ2019H304). Sí

Vertebral fracture is the most common type of osteoporotic fracture. However, the prevalence of osteoporosis and osteoporotic vertebral fractures were not explored previously in the United Arab Emirates (UAE). This study aims to describe for the first time the demographic and morphological characteristics of patients with fragility vertebral fractures in the UAE through a retrospective review of the medical records of patients with low-trauma vertebral fractures who visited two tertiary centers during 2011-2016. The sex, age at the time of fracture, nationality, body mass index (BMI), and anatomical fracture location were recorded for each patient. Overall, 143 subjects were diagnosed with low-trauma vertebral fractures in the Emirate of Abu Dhabi during 2011-2016. Of these, 98 were women (68.5%) and 45 were men (31.5%). The overall mean patient age at diagnosis was 62.5 years, and almost half were younger than 65 years. Approximately 60% of the patients were UAE nationals. Fifty-one patients (36.7%) were obese (mean BMI: 35.3 kg/m2), and women with vertebral fractures had a significantly higher mean BMI compared with men (p = 0.041). Nearly 40% of men had a normal BMI, compared with 20% of women. Most fractures were compression fractures (77.6%) in the thoracolumbar transition region. In conclusion, patients with fragility vertebral fractures were predominantly female and tended to be overweight or obese, although male patients tended to have a lower BMI than female patients.

Introduction Similar to other non-communicable diseases (NCDs), people who develop cardiovascular disease (CVD) typically have more than one risk factor. The clustering of cardiovascular risk factors begins in youth, early adulthood, and middle age. The presence of multiple risk factors simultaneously has been shown to increase the risk for atherosclerosis development in young and middle-aged adults and risk of CVD in middle age. Objective This study aimed to address the interrelationship of CVD risk factors and their accumulation in a large sample of young adults in the United Arab Emirates (UAE). Methods Baseline data was drawn from the UAE Healthy Future Study (UAEHFS), a volunteer-based multicenter study that recruits Emirati nationals. Data of participants aged 18 to 40 years was used for cross-sectional analysis. Demographic and health information was collected through self-reported questionnaires. Anthropometric data and blood pressure were measured, and blood samples were collected. Results A total of 5126 participants were included in the analysis. Comorbidity analyses showed that dyslipidemia and obesity co-existed with other cardiometabolic risk factors (CRFs) more than 70% and 50% of the time, respectively. Multivariate logistic regression analysis of the risk factors with age and gender showed that all risk factors were highly associated with each other. The strongest relationship was found with obesity; it was associated with four-fold increase in the odds of having central obesity [adjusted OR 4.70 (95% CI (4.04–5.46)], and almost three-fold increase odds of having abnormal glycemic status [AOR 2.98 (95% (CI 2.49–3.55))], hypertension (AOR 3.03 (95% CI (2.61–3.52))] and dyslipidemia [AOR 2.71 (95% CI (2.32–3.15)]. Forty percent of the population accumulated more than 2 risk factors, and the burden increased with age. Conclusion In this young population, cardiometabolic risk factors are highly prevalent and are associated with each other, therefore creating a heavy burden of risk factors. This forecasts an increase in the burden of CVD in the UAE. The robust longitudinal design of the UAEHFS will enable researchers to understand how risk factors cluster before disease develops. This knowledge will offer a novel approach to design group-specific preventive measures for CVD development.

Accurate prediction of a newborn’s birth weight (BW) is a crucial determinant to evaluate the newborn’s health and safety. Infants with low BW (LBW) are at a higher risk of serious short- and long-term health outcomes. Over the past decade, machine learning (ML) techniques have shown a successful breakthrough in the field of medical diagnostics. Various automated systems have been proposed that use maternal features for LBW prediction. However, each proposed system uses different maternal features for LBW classification and estimation. Therefore, this paper provides a detailed setup for BW estimation and LBW classification. Multiple subsets of features were combined to perform predictions with and without feature selection techniques. Furthermore, the synthetic minority oversampling technique was employed to oversample the minority class. The performance of 30 ML algorithms was evaluated for both infant BW estimation and LBW classification. Experiments were performed on a self-created dataset with 88 features. The dataset was obtained from 821 women from three hospitals in the United Arab Emirates. Different performance metrics, such as mean absolute error and mean absolute percent error, were used for BW estimation. Accuracy, precision, recall, F-scores, and confusion matrices were used for LBW classification. Extensive experiments performed using five-folds cross validation show that the best weight estimation was obtained using Random Forest algorithm with mean absolute error of 294.53 g while the best classification performance was obtained using Logistic Regression with SMOTE oversampling techniques that achieved accuracy, precision, recall and F1 score of 90.24%, 87.6%, 90.2% and 0.89, respectively. The results also suggest that features such as diabetes, hypertension, and gestational age, play a vital role in LBW classification.

IntroductionThe worldwide rising levels of physical inactivity especially in the United Arab Emirates (UAE) and the Eastern Mediterranean region are alarming. The UAE reports one of the highest rates of non-communicable disease mortality and insufficient physical activity (PA) is a major underlying cause. Therefore, action is required to reduce physical inactivity using evidence-based strategies. This study aimed to evaluate the efficacy of a worksite exercise intervention on cardiometabolic health in the UAE.Methods and analysisThis is a protocol for a pragmatic parallel randomised controlled trial with a 1:1 allocation ratio to the intervention group and delayed intervention group. A total of 150 participants will be recruited from a semigovernment telecommunications company in Dubai (UAE) after meeting the eligibility criteria. The intervention group will receive 2 hours of exercise per week during working hours for 12 weeks (maximum 1 hour/day). The intervention group will be assigned to attend personal trainer sessions in the workplace gym throughout the intervention period. After the intervention is completed, the delayed intervention group will also receive 2 hours of exercise time per week from working hours for 4 weeks. The main outcome measure is the change in the cardiometabolic risk components, that is, systolic or diastolic blood pressure, waist circumference, glycated haemoglobin, fasting plasma glucose, low-density lipoprotein cholesterol from baseline to the end of the intervention. The secondary outcome is to examine whether the workplace exercise intervention improves PA levels 4 weeks postintervention.Ethics and disseminationThe study has been approved by the Dubai Scientific Research Ethics Committee (DSREC-SR-08/2019_02). The results will be disseminated as follows: at various national and international scientific conferences; as part of a PhD thesis in Public Health at the College of Medicine and Health Sciences, UAE University; and in a manuscript submitted to a peer-reviewed journal.Trial registration numberNCT04403789.

Objective: Inflammation is a major factor in endothelial dysfunction (ED) which is the earliest predictor of cardiovascular disease and premature mortality in type 1 diabetes mellitus (T1DM) patients. This study aimed to describe the possible relationship between plasma lipids and inflammatory and ED biomarkers in young Emirati patients with and without T1DM. Methods: This case-control study included 158 patients with T1DM and 157 healthy controls from the local population of the United Arab Emirates (UAE). Anthropometric data, clinical variables, lipid profiles, liver enzymes, HbA1c, inflammatory, and ED biomarkers were measured for all participants using sophisticated techniques and assays. Results: The mean ages ± SD of patients with T1DM and healthy controls was 19.3 ± 6.4 years (59.5% females) and 9.2 ± 6.8 years (61.5% females), respectively. The mean duration of T1DM was 9.3 ± 5.7 years, with HbA1c of 8.9 ± 2.1%. BMI, WC, SBP, and DBP significantly differed between the two groups. The mean lipid profiles (HDL, TG, TC, ApoA, and ApoB), liver enzymes (GGT, ALT), inflammatory (IL-6, adiponectin, TNF-α, hs-CRP), and ED biomarker levels (ICAM-1, VCAM-1, selectin, and ET-1) were also significantly different between patients and controls. Based on Spearman’s rank and logistic regression analysis, there was a significant association between elevated lipid profile, liver enzymes, inflammatory markers, and ED markers in T1DM patients compared to controls. Among the biomarkers studied, ApoA, ApoB, and TC were significantly increased in T1DM patients compared to controls. Conclusion: This study revealed a strong association between an elevated lipid profile and inflammatory and ED markers with T1DM, which could lead to cardiovascular events in the UAE population.

BackgroundPharmacists play a unique role in integrating genomic medicine and pharmacogenomics into the clinical practice and to translate pharmacogenomics from bench to bedside. However, the literature suggests that the knowledge gap in pharmacogenomics is a major challenge; therefore, developing pharmacists’ skills and literacy to achieve this anticipated role is highly important. We aim to conceptualize a personalized literacy framework for the adoption of genomic medicine and pharmacogenomics by pharmacists in the United Arab Emirates with possible regional and global relevance.ResultsA qualitative approach using focus groups was used to design and to guide the development of a pharmacogenomics literacy framework. The Health Literacy Skills framework was used as a guide to conceptualize the pharmacogenomics literacy for pharmacists. The framework included six major components with specific suggested factors to improve pharmacists’ pharmacogenomics literacy. Major components include individual inputs, demand, skills, knowledge, attitude and sociocultural factors.ConclusionThis framework confirms a holistic bottom-up approach toward the implementation of pharmacogenomics. Personalized medicine entails personalized efforts and frameworks. Similar framework can be created for other healthcare providers, patients and stakeholders.

Focus of Presentation There is a confusion among epidemiologists, especially early-career epidemiologists, on the different definitions and use of prospective and retrospective cohort studies. There is a need for consensus by the expert community on this methodological dilemma. Findings Different Epidemiology experts define prospective and retrospective cohort studies differently. Most textbooks define prospective cohort study as one conducted when all the subjects are outcome-free while in retrospective cohort study, at least some of them have developed the outcomes, then researchers go back in time to study exposures. However, some experts define both study types based on the time of development of the research hypothesis or question in relation to data collection. Some experts consider retrospective studies to be only from records. Meanwhile, some consider any follow up study to be prospective even if historical data is used. These disparities in definitions lead to confusion among young epidemiologists. Some experts state that there is no need to differentiate between the two studies, however, we are aware of the possible bias and confounding that could occur from retrospective studies. Conclusions/Implications It has become essential for the expert community to address this methodological dilemma and to reach consensus on it. This could serve as a guide for young epidemiologists and ensure the uniformity of research worldwide. Key messages There are disparities in definitions and use of prospective and retrospective cohort studies. Hence, the expert community, especially the International Association of Epidemiology, should address this dilemma and reach a consensus to form standard guidelines.

Focus of Presentation There has been a lot of confusion among epidemiologists, especially students and early career epidemiologists, on definitions of prospective and retrospective cohort studies versus the actual practice. Many retrospective studies are reported and reviewed as prospective studies, and this is expected to lead to drawing wrong conclusions from studies, as well as leading to the disruption of the evidence-based hierarchy especially when it comes to systematic reviews and meta-analysis. There is a need, therefore, for consensus by the expert community to clarify every aspect of this issue. Findings Most epidemiological textbooks define prospective cohort study as a type of cohort study where researchers develop and conduct the study on all subjects before they start developing outcomes while in retrospective cohort study, the researchers go back in time to study exposure history for subjects whom at least some of them have developed the outcomes. Some experts, though, define both study types based on the time of development of the hypothesis or research question in relation to data collection. That is, those who develop the research question before data collection are considered to be conducting a prospective study and it is a retrospective study when developed after data collection (Miettinen, O.S. 1985). In some cases, retrospective studies are defined as the cohort studies whose data collections are from the records or historical data, while prospective studies are when data are collected prospectively (Setia M.S. 2016). Meanwhile, some experts consider any follow up study to be prospective even if historical data is used while they define retrospective studies as case control studies (Last, J.M. 2000, Doll, R. and Hill, A.B. 1954) These disparities in definitions lead to confusion among young epidemiologists as to which study type, they are conducting. This leads to the question of how important it is to differentiate the two study types. Is it really necessary? Does it affect my study results? Some experts are of the opinion that the need to differentiate between the two is minimal, as a retrospective cohort study conducted very well could be superior to an average prospective one in terms of evidence-based hierarchy. And due to the ambiguity and inconsistent nature of these labels, some even recommend abandoning the labels all together (Wylie C. E. 2015, Vandenbroucke, J.P. 1991). However, we are aware that data collected in retrospective studies might be prone to issues like incomplete records, recall bias and confounding, thereby leading to decreased internal validity of studies. This could be averted if the same study were conducted retrospectively. Conclusions/Implications It has become apparent that it is very essential for the expert community to address this methodological issue in Epidemiology and try to reach some consensus on this matter with regards to whether these subdivisions should be maintained and if so, how they should be uniformly defined and also to have a standard uniform methodological guideline that could be used internationally. This could serve as a guide for young epidemiologists and could ensure the uniformity of research worldwide. Key messages There is a confusion, especially among young epidemiologist on the definitions and use of prospective and retrospective cohort studies Expert community, especially the International Association of Epidemiology, should address these concerns and if possible, have a consensus to form a standard guideline.

Women in the Middle East and North Africa (MENA) region are burdened with several risk factors related to gestational diabetes mellitus (GDM) including overweight and high parity. We systematically reviewed the literature and quantified the weighted prevalence of GDM in MENA at the regional, subregional, and national levels. Studies published from 2000 to 2019 reporting the prevalence of GDM in the MENA region were retrieved and were assessed for their eligibility. Overall and subgroup pooled prevalence of GDM was quantified by random-effects meta-analysis. Sources of heterogeneity were investigated by meta-regression. The risk of bias (RoB) was assessed by the National Heart, Lung, and Blood Institute’s tool. One hundred and two research articles with 279,202 tested pregnant women for GDM from 16 MENA countries were included. Most of the research reports sourced from Iran (36.3%) and Saudi Arabia (21.6%), with an overall low RoB. In the 16 countries, the pooled prevalence of GDM was 13.0% (95% confidence interval [CI], 11.5–14.6%, I2, 99.3%). Nationally, GDM was highest in Qatar (20.7%, 95% CI, 15.2–26.7% I2, 99.0%), whereas subregionally, GDM was highest in Gulf Cooperation Council (GCC) countries (14.7%, 95% CI, 13.0–16.5%, I2, 99.0%). The prevalence of GDM was high in pregnant women aged ≥30 years (21.9%, 95% CI, 18.5–25.5%, I2, 97.1%), in their third trimester (20.0%, 95% CI, 13.1–27.9%, I2, 98.8%), and who were obese (17.2%, 95% CI, 12.8–22.0%, I2, 93.8%). The prevalence of GDM was 10.6% (95% CI, 8.1–13.4%, I2, 98.9%) in studies conducted before 2009, whereas it was 14.0% (95% CI, 12.1–16.0%, I2, 99.3%) in studies conducted in or after 2010. Pregnant women in the MENA region are burdened with a substantial prevalence of GDM, particularly in GCC and North African countries. Findings have implications for maternal health in the MENA region and call for advocacy to unify GDM diagnostic criteria.Systematic Review RegistrationPROSPERO CRD42018100629

Various forms of tobacco smoking and nicotine vaping tools are available on the market. This study quantified the prevalence of and identified factors associated with patterns of smoking and nicotine vaping among university students in the United Arab Emirates (UAE). A cross-sectional sample of students enrolled in three public universities was surveyed. Self-reported current smoking and nicotine vaping were recorded. Of 1123 students, 81.7% completed the online survey (mean age, 20.7 ± 3.4 (SD) years, 70.7% females). The prevalence of current smoking was 15.1% while the prevalence of current nicotine vaping was nearly 4.0%. Among current smokers, 54.7% reported conventional smoking only, 15.1% reported nicotine vaping only, and 28.8% were poly-users. Conventional midwakh (47.5%), followed by conventional shisha/waterpipe (36.7%), conventional cigarettes (36.7%), electronic shisha/waterpipe (25.2%), and electronic cigarettes (24.5%), were most commonly reported by students. Students aged 20–25 years (adjusted odds ratios (aOR): 2.08, 95% confidence interval (CI): 1.18–3.67) or &gt, 25 years (aOR: 4.24, 95% CI: 1.41–12.80) had higher odds of being current smokers compared to those aged 17–19 years. The male gender was also independently associated with higher odds of being a current smoker (aOR: 5.45, 95% CI: 3.31–8.97) as well as higher odds of smoking cigarettes, shisha, and midwakh, or nicotine vaping compared to being female. Of nicotine vaping users, 36.1% reported using nicotine vaping because they enjoyed the flavor and vaporizing experience and 34.4% used it to help them to quit smoking. A relatively high prevalence of self-reported smoking was reported among university students in the UAE. The findings also suggest that nicotine vaping use is relatively widespread, but still less common than traditional smoking. Vigilant and tailored university-based smoking control and preventive measures are warranted.

Gestational diabetes mellitus (GDM) burden is burgeoning globally. Correct knowledge about GDM among young people is paramount for timely prevention. This study assesses GDM knowledge and identifies factors associated with it among United Arab Emirates (UAE) University students. A validated self-administered questionnaire collected data from the university students. We analyzed the data for GDM knowledge status (ever heard of GDM) and GDM knowledge levels (poor, fair, and good) and conducted ordinal logistic regressions to assess for associated factors. A total of 735 students were surveyed with a mean age of 21.0 years. Of these, 72.8% had heard of GDM, and 52.9% of males versus 20.3% of female students had never heard of the condition before. Higher age (p = 0.019) and being a postgraduate student (p = 0.026) were associated with higher GDM knowledge status in males. GDM knowledge level analysis showed that 24.0%, 58.5%, and 17.5% had poor, fair, and good knowledge. The mean GDM-knowledge score was 6.3 ± 2.4 (out of 12). Being married [aOR-1.82 (95%CI 1.10–3.03)] and knowing someone who had GDM [aOR-1.78 (95%CI 1.23–2.60)] were independently associated with higher GDM knowledge levels among students. Students’ primary source of GDM knowledge was family/friends. There is an observed knowledge gap related to GDM among the students, especially males. This study urges the need to accelerate targeted GDM awareness campaigns among university students and the general population in the UAE.

Objective: This study examined the associations of sociodemographic and lifestyle factors with prepregnancy body mass index (BMI) and gestational weight gain (GWG). Methods: In the Mutaba'ah Study in the United Arab Emirates, repeated measurements throughout pregnancy from medical records were used to determine prepregnancy BMI and GWG. Associations of sociodemographic and lifestyle factors with prepregnancy BMI and GWG (separately by normal weight, overweight, and obesity status) were tested using multivariable regression models, adjusted for maternal age at delivery. Results: Among 3536 pregnant participants, more than half had prepregnancy overweight (33.2%) or obesity (26.9%), and nearly three-quarters had inadequate (34.2%) or excessive (38.2%) GWG. Higher parity (β for 1-2 to ≥5 children = 0.94 to 1.73 kg/m2), lower maternal education (β for tertiary = -1.42), infertility treatment (β = 0.69), and maternal prepregnancy active smoking (β = 1.95) were independently associated with higher prepregnancy BMI. Higher parity was associated with a lower risk for excessive GWG among women with prepregnancy normal weight (odds ratios (ORs) for 1-2 to ≥5 children = 0.61 to 0.39). Higher maternal education was negatively associated with inadequate GWG among women with normal weight and overweight (ORs for tertiary education = 0.75 and 0.69, respectively). Conclusions: Sociodemographic factors, especially parity and maternal education, were differentially associated with prepregnancy BMI and GWG adequacy across weight status.

Self-reported tobacco use is high in the male adult Emirati population (males ~36% vs. females ~3%); however, there are minimal data on tobacco use or exposure to environmental tobacco smoke (ETS) during pregnancy in the United Arab Emirates (UAE). This study investigated the prevalence of, and factors associated with, tobacco use and exposure to environmental tobacco smoke (ETS) amongst pregnant women in the UAE. Baseline cross-sectional data were analysed from the Mutaba’ah Study. Expectant mothers completed a self-administered questionnaire collecting sociodemographic information, maternal tobacco use, and ETS exposure during antenatal visits at three hospitals in Al Ain (UAE; May 2017–February 2021). Amongst 8586 women included in the study, self-reported tobacco use during pregnancy was low (0.7%), paternal tobacco use was high (37.9%), and a third (34.8%) of expectant mothers were exposed to ETS (28.0% at home only). Pregnant women who were employed (adjusted odds ratio (aOR): 1.35, 95% confidence interval (CI): 1.19–1.52), with childbirth anxiety (aOR 1.21, 95% CI 1.08–1.36), and with an increased number of adults living in the same household (aOR 1.02 95% CI 1.01–1.03) were independently more likely to be exposed to ETS. Pregnant women with higher education levels (aOR 0.84, 95% CI 0.75–0.94) and higher gravidity (aOR 0.95, 95% CI 0.92–0.99) were less likely to be exposed to ETS. Public health efforts targeting smoking cessation amongst husbands and promoting smoke-free homes are warranted to help reduce prenatal ETS exposure in the UAE.