Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions

Facile Fabrication of Fe₂O₃/TiO₂ Composite from Titanium Slag as Adsorbent for As(V) Removal from Aqueous Media

Mixed metal oxide composites have been widely used as adsorbents for the removal of heavy metal ions from wastewater. In this work, Fe2O3/TiO2 composite was sustainably prepared via the treatment of titanium slag with a low-concentration sulfuric acid solution (20%) and used for the removal of As(V) from aqueous solutions. The resulting products were characterized by X-ray diffraction (XRD), N2 adsorption−desorption, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDX). The batch adsorption was employed to investigate the removal efficiency of the Fe2O3/TiO2 adsorbent toward As(V). The Langmuir and Freundlich isotherms were plotted in order to study the adsorption process. The adsorption of As(V) on FeO3/TiO2 fitted well with the Freundlich isotherm model, suggesting a multilayer adsorption process with an adsorption capacity of 68.26 mg·g−1. The adsorption kinetics study demonstrated that the adsorption behavior of the Fe2O3/TiO2 composite for the As(V) was pseudo-second-order. With low-cost preparation and high adsorption capacity, the prepared Fe2O3/TiO2 adsorbent could be used as an effective adsorbent for As(V) removal from contaminated water sources. The approach utilized in this research is viewed as a sustainable route for creating a proficient adsorbent for the purification of water

Dynamic weighted ensemble for diarrhoea incidence predictions

Diarrhoea (DH) disease pose significant threats to national morbidity and mortality in Vietnam, especially on children. Being a climate sensitive disease, it has strong links to various meteorological factors like rainfalls or temperatures. Hence, together with global climate changes, the risk of diarrhoea has been increasing gradually while Vietnam is already a hotspot of diarrhoea worldwide. Thus, having an effective early warning system is becoming an urgent need. However, it has not been paid enough attention with very few research works, mainly focusing on quantilizing the relationships among various climate factors and diarrhoea incidences. Exploring more sophisticated machine learning techniques is therefore an interesting work towards more efficient and effective warning systems. This paper consists of two main contributions. First, many different state-of-the-art prediction models from traditional to most recent advantaged methods, e.g., SARIMA, SARIMAX, LSTM, CNN, Xgboost, SVM, LightGBM, Catboost, LightGBM, N-HiST, BlockRNN, TCN, TFT, or Transformer, are studied for predicting DH rates for a large number of locations (55 provinces) with different climates, geographics and socio-economy factors. It provides a useful view on the overall performances of different ML models on the prediction task, which is extremely useful for other researchers when developing early-warning systems for DH in other places. Second, we introduce a novel ensemble prediction model, called dynamic weighted ensemble (DWE), for further improving the DH prediction performance. DWE is a two layer ensemble approach. The first generates different meta models based on four base component models. The second layer employs a novel approach to predict the performances of all selected meta models and uses these predicted results to dynamically combine these models in a weighted scheme to produce final results. This is totally different to traditional ensemble approaches which only rely on fixed combinations of their components. To the best of our knowledge, DWE is also the first ensemble approach for diarrhoea prediction. Extensive experiments are conducted over all 55 provinces of Vietnam to demonstrate the performance of DWE and to reveal its important characteristics.</p

Frequency and management of maternal infection in health facilities in 52 countries (GLOSS): a 1-week inception cohort study

Background Maternal infections are an important cause of maternal mortality and severe maternal morbidity. We report the main findings of the WHO Global Maternal Sepsis Study, which aimed to assess the frequency of maternal infections in health facilities, according to maternal characteristics and outcomes, and coverage of core practices for early identification and management. Methods We did a facility-based, prospective, 1-week inception cohort study in 713 health facilities providing obstetric, midwifery, or abortion care, or where women could be admitted because of complications of pregnancy, childbirth, post-partum, or post-abortion, in 52 low-income and middle-income countries (LMICs) and high-income countries (HICs). We obtained data from hospital records for all pregnant or recently pregnant women hospitalised with suspected or confirmed infection. We calculated ratios of infection and infection-related severe maternal outcomes (ie, death or near-miss) per 1000 livebirths and the proportion of intrahospital fatalities across country income groups, as well as the distribution of demographic, obstetric, clinical characteristics and outcomes, and coverage of a set of core practices for identification and management across infection severity groups. Findings Between Nov 28, 2017, and Dec 4, 2017, of 2965 women assessed for eligibility, 2850 pregnant or recently pregnant women with suspected or confirmed infection were included. 70·4 (95% CI 67·7–73·1) hospitalised women per 1000 livebirths had a maternal infection, and 10·9 (9·8–12·0) women per 1000 livebirths presented with infection-related (underlying or contributing cause) severe maternal outcomes. Highest ratios were observed in LMICs and the lowest in HICs. The proportion of intrahospital fatalities was 6·8% among women with severe maternal outcomes, with the highest proportion in low-income countries. Infection-related maternal deaths represented more than half of the intrahospital deaths. Around two-thirds (63·9%, n=1821) of the women had a complete set of vital signs recorded, or received antimicrobials the day of suspicion or diagnosis of the infection (70·2%, n=1875), without marked differences across severity groups. Interpretation The frequency of maternal infections requiring management in health facilities is high. Our results suggest that contribution of direct (obstetric) and indirect (non-obstetric) infections to overall maternal deaths is greater than previously thought. Improvement of early identification is urgently needed, as well as prompt management of women with infections in health facilities by implementing effective evidence-based practices