Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Estimating cardiovascular hospitalizations and associated expenses attributable to ambient carbon monoxide in Lanzhou, China: scientific evidence for policy making

Objectives: Air pollution is an important trigger of cardiovascular disease worldwide, but few studies have determined the cardiovascular disease, health, and economic burdens attributable to ambient carbon monoxide (CO). This study aimed to examine the association between CO and CVD hospitalizations, and quantified the attributable CVD hospitalizations, associated hospital stays and hospitalization costs for CO in Lanzhou, one of the most air-polluted Chinese cities historically.Methods: Daily data on CVD hospitalizations, air pollutants, and weather records from 2013 to 2017 were obtained for Lanzhou, China. Generalized additive model with a quasi-Poisson link was used to model the association between CO and CVD hospitalizations, after controlling for other air pollutants, weather conditions, day of week, long-term trend, influenza and pneumonia incidence. The effects of CO on hospital stays and hospitalization expenses from CVD were also quantified.Results: CO concentrations below the current Chinese ambient air quality standard had a significant impact on CVD hospitalizations. Each 1 mg/m(3) increase in CO concentration on the present day and previous 4 days (lag 0-4) was associated with an 11% (95% confidence interval: 3%-20%) increase in total CVD hospitalizations. During the study period, CO was responsible for 11.74% of total CVD hospitalizations, equating to 62,792 inpatient days and 149 million RMB. Each adult patient on average spent approximately 5% of annual salary on medicine from CO-related CVD treatment during hospitalization. Maintaining the historical CO concentration within 1 to 3 mg/m(3) could avert hundreds of total CVD hospitalizations and save millions of RMB annually in Lanzhou, China.Conclusions: Exposure to low-level ambient CO concentration increased the risk of CVD hospitalizations and resulted in substantial health and economic burdens in Lanzhou, China. Our findings can be used for evidence-based practice and policy making to assess the cost-effectiveness of prevention measures. (C) 2019 Elsevier B.V. All rights reserved

Selective Hydrogenation of m-Dinitrobenzene to m-Nitroaniline over Ru-SnOx/Al2O3 Catalyst

Series catalysts of Ru-SnOx/Al2O3 with varying SnOx loading of 0–3 wt% were prepared, and their catalytic activity and selectivity have been discussed and compared for the selective hydrogenation of m-dinitrobenzene (m-DNB) to m-nitroaniline (m-NAN). The Ru-SnOx/Al2O3 catalysts were characterized by X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM) and hydrogen temperature-programmed reduction (H2-TPR) and desorption (H2-TPD). Under the modification of SnOx, the reaction activity increased obviously, and the best selectivity to m-NAN reached above 97% at the complete conversion of m-DNB. With the increasing of the SnOx loading, the amount of active hydrogen adsorption on the surface of the catalyst increased according to the H2-TPD analysis, and the electron transferred from Ru to SnOx species, as determined by XPS, inducing an electron-deficient Ru, which is a benefit for the absorption of the nitro group. Therefore, the reaction rate and product selectivity were greatly enhanced. Moreover, the Ru-SnOx/Al2O3 catalyst presented high stability: it could be recycled four times without any loss in activity and selectivity

Removal of ammonium from aqueous solutions using alkali-modified biochars

Biochars converted from agricultural residuals can effectively remove ammonium from water. This work further improved the sorption ability of biochars to aqueous ammonium through alkali modification. Three modified biochars were prepared from agricultural residuals pre-treated with NaOH solution through low-temperature (300 °C) slow pyrolysis. The modified biochars effectively removed ammonium ions from water under various conditions with relatively fast adsorption kinetics (reached equilibrium within 10 h) and extremely high adsorption capacity (>200 mg/g). The Langmuir maximum capacity of the three modified biochars were between 313.9 and 518.9 mg/g, higher than many other ammonium adsorbents. Although the sorption of ammonium onto the modified biochar was affected by pH and temperature, it was high under all of the tested conditions. Findings from this work indicated that alkali-modified biochars can be used as an alternative adsorbent for the removal of ammonium from wastewater

Effect of Phosphine Doping and the Surface Metal State of Ni on the Catalytic Performance of Ni/Al2O3 Catalyst

Ni-based catalysts as replacement for noble metal catalysts are of particular interest in the catalytic conversion of biomass due to their cheap and satisfactory catalytic activity. The Ni/SiO2 catalyst has been studied for the hydrogenolysis of glycerol, and doping with phosphorus (P) found to improve the catalytic performance significantly because of the formation of Ni2P alloys. However, in the present work we disclose a different catalytic phenomenon for the P-doped Ni/Al2O3 catalyst. We found that doping with P has a significant effect on the state of the active Ni species, and thus improves the selectivity to 1,2-propanediol (1,2-PDO) significantly in the hydrogenolysis of glycerol, although Ni-P alloys were not observed in our catalytic system. The structure and selectivity correlations were determined from the experimental data, combining the results of X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), hydrogen temperature-programmed reduction (H2-TPR) and ammonia temperature-programmed desorption (NH3-TPD). The presence of NiO species, formed from P-doped Ni/Al2O3 catalyst, was shown to benefit the formation of 1,2-PDO. This was supported by the results of the Ni/Al2O3 catalyst containing NiO species with incomplete reduction. Furthermore, the role the NiO species played in the reaction and the potential reaction mechanism over the P-doped Ni/Al2O3 catalyst is discussed. The new findings in the present work open a new vision for Ni catalysis and will benefit researchers in designing Ni-based catalysts

A Comprehensive Analysis Identified Hub Genes and Associated Drugs in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common neurodegenerative disease among the elderly and has become a growing global health problem causing great concern. However, the pathogenesis of AD is unclear and no specific therapeutics are available to provide the sustained remission of the disease. In this study, we used comprehensive bioinformatics to determine 158 potential genes, whose expression levels changed between the entorhinal and temporal lobe cortex samples from cognitively normal individuals and patients with AD. Then, we clustered these genes in the protein-protein interaction analysis and identified six significant genes that had more biological functions. Besides, we conducted a drug-gene interaction analysis of module genes in the drug-gene interaction database and obtained 26 existing drugs that might be applied for the prevention and treatment of AD. In addition, a predictive model was built based on the selected genes using different machine learning algorithms to identify individuals with AD. These findings may provide new insights into AD therapy