Assessment of Sodium Knowledge and Urinary Sodium Excretion among Regions of the United Arab Emirates: A Cross-Sectional Study

Non-communicable diseases (NCDs) such as cardiovascular disease, cancer and diabetes, are increasing worldwide and cause 65% to 78% of deaths in the Gulf Cooperation Council (GCC). A random sample of 477 healthy adults were recruited in the United Arab Emirates (UAE) in the period March-June 2015. Demographic, lifestyle, medical, anthropometric and sodium excretion data were collected. A questionnaire was used to measure knowledge, attitude and practice regarding salt. Mean sodium and potassium excretion were 2713.4 ± 713 mg/day and 1803 ± 618 mg/day, respectively, significantly higher than the World Health Organization (WHO) recommendations for sodium (2300 mg/day) and lower for potassium (3150 mg/day). Two-thirds (67.4%) exceeded sodium guidelines, with males 2.6 times more likely to consume excessively. The majority of the participants add salt during cooking (82.5%) and whilst eating (66%), and 75% identified processed food as high source of salt. Most (69.1%) were aware that excessive salt could cause disease. Most of the UAE population consumes excess sodium and insufficient potassium, likely increasing the risk of NCDs. Despite most participants being aware that high salt intake is associated with adverse health outcomes, this did not translate into salt reduction action. Low-sodium, high-potassium dietary interventions such as the Mediterranean diet are vital in reducing the impact of NCDs in the UAE

Impact of Skills for Change Program on metabolic control, diet and physical activity levels in adults with type 2 diabetes: A cluster randomized trial

Background: Type 2 diabetes mellitus is highly prevalent in the Arab Gulf countries. Despite this, limited culturally-adapted lifestyle intervention studies have been conducted in this region. Methods: In this culturally adapted 12-month cluster randomized trial, 382 patients with type 2 diabetes, aged 20–70 years were recruited from 6 public healthcare centers (3 interventions and 3 controls) in Al Ain, United Arab Emirates. The primary outcome of this study was a change in hemoglobin A1c (HbA1c). The secondary outcomes were Body Mass Index (BMI), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, total cholesterol, dietary intake, and physical activity levels. A diet and physical activity intervention, guided by the social cognitive theory, was delivered individually and in group format to the intervention group. The control group continued receiving only their usual diabetes management care. The data were collected at baseline and 1 year after participation. Results: The mean baseline HbA1c levels of the control and the intervention groups were 7.45 ± 0.11% and 7.81 ± 0.11%, respectively. At the end of the 12-month intervention, there was no significant difference in the changes of mean HbA1c between the intervention and the control groups. On the other hand, BMI and daily caloric intake were significantly decreased in the intervention compared to the control group by 1.18 kg/m2 (95% CI: -1.78 − -0.60) and 246 kcal (95% CI: -419.52 − -77.21), respectively, after controlling for age, gender, education, marital status, duration since diabetes diagnosis, diabetes treatment, treatment clinic, and baseline values. Sitting time during the week-end was significantly lower, difference 52.53 minutes (95% CI: 93.93 − -11.14). Conclusions: This community-based lifestyle intervention for patients with baseline HbA1c <8% did not result in a significant decrease of HbA1c but reduced caloric intake, body weight, and weekend inactivity after controlling for the covariates. Trial registration: This trial was registered on February 11, 2020 with Clinicaltrials.gov (NCT04264793)

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Differential diagnosis of perinatal hypophosphatasia: radiologic perspectives

Perinatal hypophosphatasia (HPP) is a rare, potentially life-threatening, inherited, systemic metabolic bone disease that can be difficult to recognize in utero and postnatally. Diagnosis is challenging because of the large number of skeletal dysplasias with overlapping clinical features. This review focuses on the role of fetal and neonatal imaging modalities in the differential diagnosis of perinatal HPP from other skeletal dysplasias (e.g., osteogenesis imperfecta, campomelic dysplasia, achondrogenesis subtypes, hypochondrogenesis, cleidocranial dysplasia). Perinatal HPP is associated with a broad spectrum of imaging findings that are characteristic of but do not occur in all cases of HPP and are not unique to HPP, such as shortening, bowing and angulation of the long bones, and slender, poorly ossified ribs and metaphyseal lucencies. Conversely, absent ossification of whole bones is characteristic of severe lethal HPP and is associated with very few other conditions. Certain features may help distinguish HPP from other skeletal dysplasias, such as sites of angulation of long bones, patterns of hypomineralization, and metaphyseal characteristics. In utero recognition of HPP allows for the assembly and preparation of a multidisciplinary care team before delivery and provides additional time to devise treatment strategies