Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4 (62.3 (55.1�70.8) million) to 6.4 (58.3 (47.6�70.7) million), but is predicted to remain above the World Health Organization�s Global Nutrition Target of <5 in over half of LMICs by 2025. Prevalence of overweight increased from 5.2 (30 (22.8�38.5) million) in 2000 to 6.0 (55.5 (44.8�67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic. © 2020, The Author(s)

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Global, regional, and national burden of suicide mortality 1990 to 2016: Systematic analysis for the Global Burden of Disease Study 2016

Objectives To use the estimates from the Global Burden of Disease Study 2016 to describe patterns of suicide mortality globally, regionally, and for 195 countries and territories by age, sex, and Socio-demographic index, and to describe temporal trends between 1990 and 2016. Design Systematic analysis. Main outcome measures Crude and age standardised rates from suicide mortality and years of life lost were compared across regions and countries, and by age, sex, and Socio-demographic index (a composite measure of fertility, income, and education). Results The total number of deaths from suicide increased by 6.7 (95 uncertainty interval 0.4 to 15.6) globally over the 27 year study period to 817 000 (762 000 to 884 000) deaths in 2016. However, the age standardised mortality rate for suicide decreased by 32.7 (27.2 to 36.6) worldwide between 1990 and 2016, similar to the decline in the global age standardised mortality rate of 30.6. Suicide was the leading cause of age standardised years of life lost in the Global Burden of Disease region of high income Asia Pacific and was among the top 10 leading causes in eastern Europe, central Europe, western Europe, central Asia, Australasia, southern Latin America, and high income North America. Rates for men were higher than for women across regions, countries, and age groups, except for the 15 to 19 age group. There was variation in the female to male ratio, with higher ratios at lower levels of Socio-demographic index. Women experienced greater decreases in mortality rates (49.0, 95 uncertainty interval 42.6 to 54.6) than men (23.8, 15.6 to 32.7). Conclusions Age standardised mortality rates for suicide have greatly reduced since 1990, but suicide remains an important contributor to mortality worldwide. Suicide mortality was variable across locations, between sexes, and between age groups. Suicide prevention strategies can be targeted towards vulnerable populations if they are informed by variations in mortality rates. © Published by the BMJ Publishing Group Limited

Author Correction: Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017 (Nature Medicine, (2020), 26, 5, (750-759), 10.1038/s41591-020-0807-6)

An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s)

Author Correction: Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017 (Nature Medicine, (2020), 26, 5, (750-759), 10.1038/s41591-020-0807-6)

An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s)

Driver Drowsiness Detection Study using Heart Rate Variability analysis in Virtual Reality Environment

Introduction Mobility and road safety is one of the grand challenges that Qatar is facing during the last decade. There are many ways to enhance the road safety. One way is to characterize the factors contributing to the road fatalities. According to Transport Accident Commission, about 20% of fatal road accidents are caused by driver fatigue [1]. As reported by Monthly Qatar Statistics in [2], the total number of deaths for the first 8 months of the current year is 116. Thus, around 23 of the casualties are caused by driver fatigue. According to the U.S. Department of Transportation's NHTSA, in 2016 the number of fatalities involving drowsy driver is 803, which is 2.1% of total fatalities in the same year in US [3]. Therefore, it is essential to design and implement an embedded system in vehicles that can analyze, detect, and recognize the driver's state. The main aim of this project is to detect and recognize different drowsiness states using electrocardiogram (ECG) based Heart Rate Variability (HRV) analysis through heartbeats data acquisition while he/she is driving the car in different timings of the day. Then an alarm is produced before the driver's situation reaches the dangerous case that might lead him/her to involve in an accident. Background A driver's drowsiness state can be detected through different methods. One of the most accurate methods is to get the HRV information acquired from Electrocardiogram (ECG) signal helps to identify different states like awake, dizziness, drowsiness and sleep behind the steering. HRV describes the involuntary nervous function, which is in fact the R-to-R interval (RRI) variations of an acquired ECG signal [4]. By identifying the RRI as well as the distance between the RR peaks, we can decide if the driver is in drowsy state or not, by analyzing HRV time and frequency domain features. Low Frequency (LF) band (0.04-0.15 Hz) describes the sympathetic and parasympathetic activities of the heart activity whereas; High Frequency (HF) band (0.15-0.4 Hz) describes only the parasympathetic activities of the heart activity [4]. The LF/HF ratio reflects the differences between awake and drowsy states while the ratio was decreasing gradually from the awake state to drowsy state [5-6].Method A portable wireless BioRadio (Fig.2 A) (Great Lakes NeuroTechnologies, Inc.) Electrocardiogram (ECG) system was used with three Ag/AgCl electrodes attached to a participant's chest. The points of attachment are (i) two electrodes under the right and left collarbone, and (ii) one electrode under the lowest left rib bone of the participant. ECG signal was band passed through a filter (0.05-100 Hz) digitized at a sampling frequency of 500 Hz with 12-bit resolution to be displayed on the device GUI software BioCapture. Data were stored from BioCapture software on the hard disk of an Intel Core i7 Personal Computer for off line analysis. The simulation of highway driving was created in virtual reality 3D cave environment (Fig. 2B) (in VR lab, Research Building, Qatar University). Simulation scenario was a two-way highway with two lanes in each direction, low density of traffic, late afternoon and/night environment, path with no sharp curves and rural environment with far apart trees. ECG data were recorded from three subjects while the subjects were driving monotonously a car in VR environment during active and drowsy states. A camera from the front was used to detect the drowsiness stages, and to segment the ECG data based on drowsiness. ECG data of each subject was exported using the Bio-Capture software and segmented using CSV splitter to analyze the data by Kubois software. ECG signal was recorded from each subject for one hour approximately until the subject becomes drowsy. The one-hour sample data was splitted into six segments, each with 10 minutes duration. This was done to make the analysis of each sample easier and to be able to specify and identify exactly the time when the subject was awake and/or drowsy. Result and Discussion Fig. 3 shows the sample ECG trace from subject one and selected RR intervals were calculated using Kubios HRV software and the RR series was produced by interpolation. This RR time series was used to calculate heart rate (HR) and HRV using the same software. The RR time series was used to calculate the power spectral density (PSD) by applying the Fast Fourier Transform (FFT) method to identify the LF and HF frequency component of the HRV. Figure 4 shows the PSD averaged over trials for sample participants in case of active and drowsy states. As it can be seen from Fig. 4, there is a significant difference in the LF/HF ratios, as it decreased drastically from 4.164 (Fig. 4A) when subject was awake to 1.355 (Fig. 4B) when subject was drowsy. In addition, HF and LF alone can be taken as indicators for drowsiness. The HF increased from 163 ms2 when subject was awake to 980 ms2 when subject was drowsy. Moreover, the LF value also increased from 679 to 1328 ms2. The summary of the LF/HF for different participants are shown in Table 1. Table 1 clearly shows that LF/HF is higher for all the subjects during their active states and the ratio is decreasing, as the subject was getting drowsy. This result is in line with the findings of other researchers.Conclusion It can be summarized from the findings from this experiment that the HRV based drowsiness detection technique can be implemented in single board computer to provide a portable solution to be deployed in the car. Depending on the sleep stages detected through HRV analysis, the driver can be alerted through either piezoelectric sensor or audible alerting message, which will help to reduce significant road accidents.qscienc

The efficacy and safety of treating hepatitis C in patients with a diagnosis of schizophrenia

Treating chronic hepatitis C with pegylated interferon alpha may induce or exacerbate psychiatric illness including depression, mania and aggressive behaviour. There is limited data regarding treatment in the context of chronic schizophrenia. We sought to establish the safety and efficacy of treating patients with schizophrenia. Patient and treatment data, prospectively collected on the Scottish hepatitis C database, were analysed according to the presence or absence of a diagnosis of schizophrenia. Time from referral to treatment, and the proportion of patients commencing treatment in each group, was calculated. Outcomes including sustained viral response rates, reasons for treatment termination and adverse events were compared. Of 5497 patients, 64 (1.2%) had a diagnosis of schizophrenia. Patients with schizophrenia (PWS) were as likely to receive treatment as those without [28/61(46%) vs 1639/4415 (37%) P = 0.19]. Sustained viral response (SVR) rates were higher in PWS [21/25 (84%) vs 788/1453 (54%) P &#60; 0.01]. SVR rates by genotype were similar [4/8 (50%) vs 239/684 (35%) Genotype 1 (P = 0.56), 17/17 (100%) vs 599/742 (81%) non-Genotype 1 (P = 0.09)]. Adverse events leading to cessation of treatment were comparable [2/25(8%) vs 189/1453 (13%) P: 0.66]. Patients with schizophrenia are good candidates for hepatitis C treatment, with equivalent SVR and treatment discontinuation rates to patients without schizophrenia