Hygiene and environmental health advances最新文献

Fine particulate matter (PM_2.5) exposure can cause premature death and harmful chronic disease such as diabetes. The U.S. Environmental Protection Agency (EPA) sets annual PM_2.5 standards to reduce these negative health effects. Currently, annual average exposure over 12 µg/m³ is considered unhealthy. This study tests whether individuals living in locations exposed to elevated ambient levels of PM_2.5 concentrations were more likely to self-report diabetes. We examined the association of long-term exposure to PM_2.5 and diabetes at enrollment (2002–2009) in a cohort of 44,610 individuals residing in 12 states, recruited into the Southern Community Cohort Study (SCCS). Annual average PM_2.5 was estimated using remotely sensed satellite data integrated with ground monitoring data at participants’ residence in urban and rural locations. We used multilevel mixed-effects logistic regression models to estimate the associations between self-reported diabetes and historical exposure to elevated ambient levels of PM_2.5. We found a 10.1% increase in odds of reported diabetes with exposure to unhealthful levels of PM_2.5 exposure (>12 µg/m³ at enrollment) compared to respondents living in areas with lower annual PM_2.5 concentrations. Participants with medical histories of hypertension, hypercholesterolemia, and smoking had an overall 384% higher odds of reported diabetes than those without these clinical risk factors. Black participants were more likely to live in locations with higher ambient PM_2.5 concentrations, report high levels of clinical risk factors, and had a 29.1% increase in odds of reported diabetes than Whites. In SCCS participants, exposures to high ambient levels of PM_2.5 were associated with self-reported diabetes at enrollment. Reduction in PM_2.5 standards for the U.S. are recommended.

A zebrafish behavioral model is prevalent and has potential to be an important component of chemical screening and toxicity evaluations. However, applications of such zebrafish behavioral assays remain limited because of flaws in monitoring procedures and designs and inconsistent test methodology among published studies. In the present study, a behavioral assay method based on zebrafish larvae was established for rapid chemical toxicity evaluation, which included the optimization of test conditions and the development of behavioral parameters, such as accumulated distance, frequency of active state, acceleration and mobility. To validate the reliability and investigate the specificity of the method developed, the behavioral effects were evaluated for a set of 28 chemicals (flame retardants, pesticides, fungicides or heavy metals) typically reported in the environment and showing effects by various modes of action (MOAs). Our results showed that the most suitable container and volume for behavioral tests of zebrafish larvae was 24-well plate containing 8-mm depth of solution, and the most appropriate developmental period for monitoring was at 5 days post-fertilization (dpf). Chemical exposure led to various dose-dependent responses of the behavioral parameters via different MOAs, e.g. estrogenic chemicals caused hyperactivity through neurodevelopment disturbance and neurotoxic chemicals led to hypoactivity through disruption of nerve signal transmission. Our results suggested that the optimized behavior monitioring method have the potential for identification and classification of neurotoxic chemicals.

As an alternative to legacy perfluorooctane sulfonate (PFOS), the wide usage of chlorinated polyfluoroalkyl ether sulfonic acid (Cl-PFESA) in China has generated considerable concerns. The study aimed to investigate the associations between cord serum emerging Cl-PFESA (6:2 Cl-PFESA and 8:2 Cl-PFESA) levels and suboptimal birth size, including low birth weight (LBW), macrosomia, small or large for gestational age (SGA or LGA) among 1048 newborns in Wuhan, China. 6:2 Cl-PFESA and 8:2 Cl-PFESA were 0.76 ng/mL and 0.03 ng/mL, respectively, higher than previously reported levels in newborns from other cities in China. We did not find significant associations between the Cl-PFESAs and suboptimal birth size when considering each Cl-PFESA as a single exposure. However, when integrating emerging Cl-PFESAs and legacy PFASs (PFOS and perfluorooctanoate acid (PFOA)) as a mixture using Bayesian kernel machine regression (BKMR) models, we found that the mixture of legacy PFASs and emerging Cl-PFESAs had inverse associations with SGA and LGA. Two legacy PFASs and two Cl-PFESAs had similar contributions to the association with SGA, whereas the majority of the association with LGA was driven by PFOS. The results demonstrated these legacy PFASs were still the predominant PFASs associated with suboptimal birth size while emerging Cl-PFESAs had a less but nonnegligible contribution to the association with SGA. Further studies in different regions with varied Cl-PFESA levels are needed to replicate the associations.

Introduction

Policy responses to the COVID-19 pandemic, such as the NY on Pause stay-at-home order (March 22 – June 8, 2020), substantially reduced traffic and traffic-related air pollution (TRAP) in New York City (NYC). We evaluated the magnitude of TRAP decreases and examined the role of modifying factors such as weekend/weekday, road proximity, location, and time-of-day.

Methods

Hourly nitrogen dioxide (NO₂) concentrations from January 1, 2018 through June 8, 2020 were obtained from the Environmental Protection Agency's Air Quality System for all six hourly monitors in the NYC area. We used an interrupted time series design to determine the impact of NY on Pause on NO₂ concentrations, using a mixed effects model with random intercepts for monitor location, adjusted for meteorology and long-term trends. We evaluated effect modification through stratification.

Results

NO₂ concentrations decreased during NY on Pause by 19% (-3.2 ppb, 95% confidence interval [CI]: -3.5, -3.0), on average, compared to pre-Pause time trends. We found no evidence for modification by weekend/weekday, but greater decreases in NO₂ at non-roadside monitors and weak evidence for modification by location. For time-of-day, we found the largest decreases for 5 am (27%, -4.5 ppb, 95% CI: -5.7, -3.3) through 7 am (24%, -4.0 ppb, 95% CI: -5.2, -2.8), followed by 6 pm and 7 pm (22%, -3.7 ppb, 95% CI: -4.8, -2.6 and 22%, -4.8, -2.5, respectively), while the smallest decreases occurred at 11 pm and 1 am (both: 11%, -1.9 ppb, 95% CI: -3.1, -0.7).

Conclusion

NY on Pause's impact on TRAP varied greatly diurnally. Decreases during early morning and evening time periods are likely due to decreases in traffic. Our results may be useful for planning traffic policies that vary by time of day, such as congestion tolling policies.

Organophosphate (OP) insecticides represent some of the most common environmental contaminants in the United States. Organophosphate insecticide use has been associated with numerous adverse health outcomes, including hypertension (HTN) and metabolic syndrome (MetS), but results from current studies are conflicting and inconclusive. In a study of 916 U.S. adults from the 2015–2016 NHANES cycle, we investigated the association between five dialkyl phosphate (DAP) metabolites of OP insecticides and blood pressure parameters (systolic blood pressure, diastolic blood pressure, pulse pressure, mean arterial pressure, HTN), as well the association between total body burden of DAPs with HTN and MetS. Weighted, multivariable linear regression revealed significant, inverse associations between diethylphosphate and systolic blood pressure (β= -0.16 p = 0.02), diethylthiophosphate and systolic blood pressure (β= -0.91 p = 0.01), total DAP exposure and systolic blood pressure (β= -0.13, p = 0.04), and between dimethylphosphate and diastolic blood pressure (β= -0.15, p = 0.0075). No significant associations were observed between total DAP exposure and odds of HTN. We additionally modeled the odds of abnormally high pulse pressure given specific quartile of total DAP exposure. Results showed a significant association between diethylphosphate and odds of abnormal pulse pressure (OR=1.29, 95% CI[1.01,1.65]), and between total DAP exposure and odds of abnormal pulse pressure (OR=1.05, 95% CI[1.03,1.10]). Lastly, we found that adults in the 3rd quartile of OP metabolite exposure had a 3.61 increased odds of having MetS when compared to individuals in the 1st quartile (OR=3.61, 95% CI[1.32,9.85]).

Our preliminary findings support data from previous studies suggesting a role for OP insecticides in the pathogenesis of blood pressure dysregulation and MetS. Future studies are warranted to corroborate these findings, determine population-level clinical significance, and to elucidate potential mechanisms explaining these associations.

Background

Research is lacking in examining how multiple climate factors affect the incidence of seasonal influenza. We investigated the associations between El Niño Southern Oscillation (ENSO), meteorological factors, and influenza incidence in New York State, United States.

Method

We collected emergency department visit data for influenza from the New York State Department of Health. ENSO index was obtained from the National Oceanic and Atmospheric Administration. Meteorological factors, Google Flu Search Index (GFI), and Influenza-like illness (ILI) data in New York State were also collected. Wavelet analysis was used to quantitatively estimate the coherence and phase difference of ENSO, temperature, precipitation, relative humidity, and absolute humidity with emergency department visits of influenza in New York State. Generalized additive models (GAM) were employed to examine the exposure-response relationships between ENSO, weather, and influenza. GFI and ILI data were used to simulate synchronous influenza visits.

Results

The influenza epidemic in New York State had multiple periodic and was primarily on the 1-year scale. The incidence of influenza closely followed the low ENSO index by an average of two months, and the lag period of ENSO on influenza was shorter during 2015–2018. Low temperature in the previous 2 weeks and low absolute humidity in the prior week were positively associated with influenza incidence in New York State. We found an l-shaped association between ENSO index and influenza, a parabolic relationship between temperature in the previous two weeks and influenza, and a linear negative association between absolute humidity in the previous week and influenza. The simulation models including GFI and ILI had higher accuracy for influenza visit estimation.

Conclusions

Low ENSO index, low temperature, and low absolute humidity may drive the influenza epidemics in New York State. The findings can help us deepen the understanding of the climate-influenza association, and help to develop an influenza forecasting model.

The effects of environmental factors on the spread of the CoViD-19 pandemic have been widely debated in the scientific literature. The results are important for understanding the outbreak dynamics and for defining health measures of prevention and containment. Using multivariate autoregressive (AR) models and robust statistics of causality, this paper analyzes the effect of 19 time series (10 physical and 9 social) on 3 daily CoViD-19 series (infected, hospitalized, deaths) in the Milan area for about 16 months. Robust M-estimation shows the weak effect of climatic and pollution factors, while authority restrictions, people mobility, smart working and vaccination rate have a significant impact. In particular, the vaccination campaign is important for reducing hospitalizations and deaths.

Air pollution is associated with a broad spectrum of health conditions. Among the reported associations are central nervous system effects, suggesting that air pollution may also affect human behavior and reaction time, which could in turn increase likelihood of injury. Injuries impose a significant public health and economic toll, but to our knowledge the relationship with air pollution has not been examined. This study investigated associations between air pollution and emergency department (ED) visits for injury and poisoning in two Canadian cities (Edmonton, Toronto). Daily concentrations of carbon monoxide, ozone, sulfur dioxide, nitrogen dioxide, and fine particulate matter (PM_2.5), and two air quality indexes (AQHI, AQHIX; incorporating O₃, NO₂, and PM_2.5), were considered. A time-stratified case-crossover design and conditional Poisson regression models were used to study short-term exposure effects (0 to 14 day lags). The analysis was done by sex, age group, and season. Significant positive associations were observed in both cities, albeit with some differences in the pattern of effects across strata. Relative risks (RR) and 95% confidence intervals (CI) for an interquartile range (IQR) increase of NO₂ (IQR=13.0 ppb, Edmonton) in cold season (October-March) for male were RR=1.012 (95% CI: 1.005, 1.018), 1.025 (1.018, 1.031), 1.026 (1.020, 1.033), and 1.025 (1.019, 1.032), for lags from 0 to 3 days, respectively. The corresponding results in Toronto (IQR=8.8 ppb) were: 1.010 (1.004, 1.017), 1.007 (1.000, 1.013), 1.009 (1.003, 1.016), and 1.007 (1.000, 1.013). The data suggest a potential association between air pollution and increased number of ED visits for injury.

This study aimed to determine the polychlorinated biphenyl (PCB) concentrations in the ambient air and in face masks of different configurations and to reveal how much masks protect from cancer risk. The total concentrations of 43 PCB congeners (∑₄₃PCBs) in the particulate phase, measured with a high-volume air sampler (HVAS), were 169.2±30.7 pg/m³ and the ∑₄₃PCBs concentrations in surgical masks were found to be 201.6±66.6 pg/m³. Similarly, the ∑₄₃PCBs concentrations in double surgical masks were 297.7±62.3 pg/m³ and 126.7±31.7 pg/m³ in non-surgical masks (cloth masks). A typical surgical mask consists of three layers (outer, filter and inner). The ∑₄₃PCBs concentrations in the outer, filter and inner layers were 273.5±8.8, 199.1±25.7 and 132.1±25.9 pg/m³, respectively. Finally, it has been determined how much the masks reduce the risk of cancer that may occur through inhalation of PCBs. According to the results, the mask with the lowest protection was the cloth mask, while the mask with the highest protection was the double surgical mask.

Food poisoning is a major public health concern. This study employs a systematic review and meta-analysis to summarise and parameterise microbial densities and isolates in ready-to-eat-foods in Bayelsa State, Nigeria. A random effect meta-analysis model is used to compare the microbial density of these foods across the various locations and occurrence rate of the commonly isolated microbes. Whereas meta-analysis results for total heterotrophic bacteria range from 3.65–6.58 Log CFU/g with a p = 0.01 measure of heterogeneity, I² =61% and overall effect being insignificantly different (p = 0.73), total fungi range from 3.10–4.03 Log CFU/g with a p = 0.92 measure of heterogeneity, I² =0% and overall effect being significantly different (p = 0.0001). The measure of heterogeneity for the microbial diversity is p = 0.22, I² =24% and overall effect is insignificant (p = 0.51). 22 microbial genera are isolated and Staphylococcus aureus, Escherichia coli and Aspergillus species depict the highest occurrence rate of 90.48 - 100%, 82.08–88.57% and 57.14- 100% respectively. The availability of these microbial diversities suggests a possible risk of food-borne diseases, hence, the need [i] to enlighten the preparers, vendors and consumers of ready-to-eat foods on the health threats posed by microorganisms found in the foods, [ii] for surveillance of ready-to-eat foods in the study area by appropriate regulatory agencies, and [iii] for vendors to improve on their storage and packaging materials as well as make provision for sources of heat in show glasses in order to retain the freshness of cooked food over prolonged periods.