Journal: Environment international
Soils in tropical and temperate locations are known to be a sink for the genetic potential of anthropogenic-driven acquired antibiotic resistance (AR). In contrast, accumulation of acquired AR is less probable in most Polar soils, providing a platform for characterizing background resistance and establishing a benchmark for assessing AR spread. Here, high-throughput qPCR and geochemistry were used to quantify the abundance and diversity of both antibiotic resistance genes (ARGs) and selected mobile genetic elements (MGEs) across eight soil clusters in the Kongsfjorden region of Svalbard in the High Arctic. Relative ARG levels ranged by over two orders of magnitude (10-6 to 10-4 copies/16S rRNA gene copy), and showed a gradient of potential human and wildlife impacts across clusters as evidenced by altered geochemical conditions and increased “foreign” ARG abundances (i.e., allochthonous), including blaNDM-1. Impacted clusters exhibited 100× higher total ARGs and MGEs in tandem with elevated secondary nutrients, especially available P that is typically low and limiting in Arctic soils. In contrast, ARGs in less-impacted clusters correlated strongly to local soil lithology. The most plausible source of exogenous P and allochthonous ARGs in this region is bird and other wildlife guano, disseminated either by local human wastes or via direct carriage and deposition. Regardless of pathway, accumulation of apparent allochthonous ARGs and MGEs in High Arctic soils is concerning, highlighting the importance of characterizing Arctic sites now to establish benchmarks for tracking AR spread around the world.
Preliminary studies suggest that offspring to mothers living near oil and natural gas (O&G) well sites are at higher risk of congenital heart defects (CHDs).
Plastics contain a complex mixture of known and unknown chemicals; some of which can be toxic. Bioplastics and plant-based materials are marketed as sustainable alternative to conventional plastics. However, little is known with regard to the chemicals they contain and the safety of these compounds. Thus, we extracted 43 everyday bio-based and/or biodegradable products as well as their precursors, covering mostly food contact materials made of nine material types, and characterized these extracts using in vitro bioassays and non-target high-resolution mass spectrometry. Two-third (67%) of the samples induced baseline toxicity, 42% oxidative stress, 23% antiandrogenicity and one sample estrogenicity. In total, we detected 41,395 chemical features with 186-20,965 features present in the individual samples. 80% of the extracts contained >1000 features, most of them unique to one sample. We tentatively identified 343 priority compounds including monomers, oligomers, plastic additives, lubricants and non-intentionally added substances. Extracts from cellulose- and starch-based materials generally triggered a strong in vitro toxicity and contained most chemical features. The toxicological and chemical signatures of polyethylene (Bio-PE), polyethylene terephthalate (Bio-PET), polybutylene adipate terephthalate (PBAT), polybutylene succinate (PBS), polylactic acid (PLA), polyhydroxyalkanoates (PHA) and bamboo-based materials varied with the respective product rather than the material. Toxicity was less prevalent and potent in raw materials than in final products. A comparison with conventional plastics indicates that bioplastics and plant-based materials are similarly toxic. This highlights the need to focus more on aspects of chemical safety when designing truly “better” plastic alternatives.
The present study investigates the relationship between night-time screen-based media devices (SBMD) use, which refers to use within 1 h before sleep, in both lit and dark rooms, and sleep outcomes and health-related quality of life (HRQoL) among 11 to 12-year-olds.
People with low income often experience higher exposures to air pollutants. We compared the exposure to particulate matter (PM1, PM2.5 and PM10), Black Carbon (BC) and ultrafine particles (PNCs; 0.02-1μm) for typical commutes by car, bus and underground from 4 London areas with different levels of income deprivation (G1 to G4, from most to least deprived). The highest BC and PM concentrations were found in G1 while the highest PNC in G3. Lowest concentrations for all pollutants were observed in G2. We found no systematic relationship between income deprivation and pollutant concentrations, suggesting that differences between transport modes are a stronger influence. The underground showed the highest PM concentrations, followed by buses and a much lower concentrations in cars. BC concentrations in the underground were overestimated due to Fe interference. BC concentrations were also higher in buses than cars because of a lower infiltration of outside pollutants into the car cabin. PNCs were highest in buses, closely followed by cars, but lowest in underground due to the absence of combustion sources. Concentration in the road modes (car and bus) were governed by the traffic conditions (such as traffic flow interruptions) at the specific road section. Exposures were reduced in trains with non-openable windows compared to those with openable windows. People from less income-deprived areas have a predominant use of car, receiving the lowest doses (RDD<1μgh(-1)) during commute but generating the largest emissions per commuter. Conversely, commuters from high income-deprived areas have a major reliance on the bus, receiving higher exposures (RDD between 1.52 and 3.49μgh(-1)) while generating less emission per person. These findings suggest an aspect of environmental injustice and a need to incorporate the socioeconomic dimension in life-course exposure assessments.
Endocrine disrupting chemicals (EDCs) are xenobiotics with the ability to interfere with hormone action, even at low levels. Prior environmental epidemiology studies link numerous suspected EDCs, including phthalates and bisphenol A (BPA), to adverse neurodevelopmental outcomes. However, results for some chemicals were inconsistent and most assessed one chemical at a time.
Strategies to protect building occupants from the risk of acute respiratory infection (ARI) need to consider ventilation for its ability to dilute and remove indoor bioaerosols. Prior studies have described an association of increased self-reported colds and influenza-like symptoms with low ventilation but have not combined rigorous characterization of ventilation with assessment of laboratory confirmed infections. We report a study designed to fill this gap. We followed laboratory confirmed ARI rates and measured CO2 concentrations for four months during the winter-spring of 2018 in two campus residence halls: (1) a high ventilation building (HVB) with a dedicated outdoor air system that supplies 100% of outside air to each dormitory room, and (2) a low ventilation building (LVB) that relies on infiltration as ventilation. We enrolled 11 volunteers for a total of 522 person-days in the HVB and 109 volunteers for 6069 person-days in the LVB, and tested upper-respiratory swabs from symptomatic cases and their close contacts for the presence of 44 pathogens using a molecular assay. We observed one ARI case in the HVB (0.70/person-year) and 47 in the LVB (2.83/person-year). Simultaneously, 154 CO2 sensors distributed primarily in the dormitory rooms collected 668,390 useful data points from over 1 million recorded data points. Average and standard deviation of CO2 concentrations were 1230 ppm and 408 ppm in the HVB, and 1492 ppm and 837 ppm in the LVB, respectively. Importantly, this study developed and calibrated multi-zone models for the HVB with 229 zones and 983 airflow paths, and for the LVB with 529 zones and 1836 airflow paths by using a subset of CO2 data for model calibration. The models were used to calculate ventilation rates in the two buildings and potential for viral aerosol migration between rooms in the LVB. With doors and windows closed, the average ventilation rate was 12 L/s in the HVB dormitory rooms and 4 L/s in the LVB dormitory rooms. As a result, residents had on average 6.6 L/(s person) of outside air in the HVB and 2.3 L/(s person) in the LVB. LVB rooms located at the leeward side of the building had smaller average ventilation rates, as well as a somewhat higher ARI incidence rate and average CO2 concentrations when compared to those values in the rooms located at the windward side of the building. Average ventilation rates in twenty LVB dormitory rooms increased from 2.3 L/s to 7.5 L/s by opening windows, 3.6 L/s by opening doors, and 8.8 L/s by opening both windows and doors. Therefore, opening both windows and doors in the LVB dormitory rooms can increase ventilation rates to the levels comparable to those in the HVB. But it can also have a negative effect on thermal comfort due to low outdoor temperatures. Simulation results identified an aerobiologic pathway from a room occupied by an index case of influenza A to a room occupied by a possible secondary case.
Climate change refers to long-term shifts in weather conditions and patterns of extreme weather events. It may lead to changes in health threat to human beings, multiplying existing health problems. This review examines the scientific evidences on the impact of climate change on human infectious diseases. It identifies research progress and gaps on how human society may respond to, adapt to, and prepare for the related changes. Based on a survey of related publications between 1990 and 2015, the terms used for literature selection reflect three aspects - the components of infectious diseases, climate variables, and selected infectious diseases. Humans' vulnerability to the potential health impacts by climate change is evident in literature. As an active agent, human beings may control the related health effects that may be effectively controlled through adopting proactive measures, including better understanding of the climate change patterns and of the compound disease-specific health effects, and effective allocation of technologies and resources to promote healthy lifestyles and public awareness. The following adaptation measures are recommended: 1) to go beyond empirical observations of the association between climate change and infectious diseases and develop more scientific explanations, 2) to improve the prediction of spatial-temporal process of climate change and the associated shifts in infectious diseases at various spatial and temporal scales, and 3) to establish locally effective early warning systems for the health effects of predicated climate change.
Temporal variation of temperature-health associations depends on the combination of two pathways: pure adaptation to increasingly warmer temperatures due to climate change, and other attenuation mechanisms due to non-climate factors such as infrastructural changes and improved health care. Disentangling these pathways is critical for assessing climate change impacts and for planning public health and climate policies. We present evidence on this topic by assessing temporal trends in cold- and heat-attributable mortality risks in a multi-country investigation.
Animal work indicates exposure to air pollutants may alter the composition of the gut microbiota. This study examined relationships between air pollutants and the gut microbiome in young adults residing in Southern California. Our results demonstrate significant associations between exposure to air pollutants and the composition of the gut microbiome using whole-genome sequencing. Higher exposure to 24-hour O3 was associated with lower Shannon diversity index, higher Bacteroides caecimuris, and multiple gene pathways, including L-ornithine de novo biosynthesis as well as pantothenate and coenzyme A biosynthesis I. Among other pollutants, higher NO2 exposure was associated with fewer taxa, including higher Firmicutes. The percent variation in gut bacterial composition that was explained by air pollution exposure was up to 11.2% for O3 concentrations, which is large compared to the effect size for many other covariates reported in healthy populations. This study provides the first evidence of significant associations between exposure to air pollutants and the compositional and functional profile of the human gut microbiome. These results identify O3 as an important pollutant that may alter the human gut microbiome.