Public health is threatened by air pollution and high temperature, especially in urban areas and areas impacted by climate change. Well-designed urban forms have co-benefits on promoting human health and mediating atmospheric environment-related threats (e.g., high temperature and air pollution). Previous studies overlooked these mediating effects of urban form on suicide mortality. This study used partial least squares modeling and countywide data in Taiwan to identify the crucial influences and pathways of urban environment, socioeconomic status, and diseases on suicide mortality. The model considered the impact of the characteristics of urban form (i.e., urban development intensity, land mix, and urban sprawl), urban industrial status (i.e., industrial level), urban greening (i.e., green coverage), disease (i.e., important diseases morbidity of human immunodeficiency virus [HIV], cerebrovascular disease [CVD], chronic liver disease and cirrhosis [CLDC], nephritis, nephrotic syndrome and nephrosis [NNSN], malignant tumor [MT]), socioeconomic status (i.e., income level and aging population rate), and the atmospheric environment (i.e., air pollution and high temperature) on suicide mortality. Optimizing land mix and minimizing urban development intensity and urban sprawl have been found to reduce suicide mortality. The mediating effect of urban form on suicide mortality originated from air pollution and high temperature, and mediating air pollution was greater than high temperature. Furthermore, industrial level, important diseases (HIV, CVD, CLDC, NNSN, and MT) morbidity, an aging population rate, air pollution, and high temperature were associated with an increase in suicide mortality, whereas green coverage and income level were associated with a reduction in suicide rates. The findings demonstrate that appropriate urban policy and urban planning may lower suicide mortality, be useful strategies for suicide prevention, and be a foundation for building a healthy city. Moreover, this study provides clarity on the complex relationship of suicide and the urban environment while identifying crucial factors.

Amyl salicylate (AS) is a fragrance massively used as a personal care product and following the discharged in wastewaters may end up in the aquatic environment representing a potential threat for the ecosystem and living organisms. AS was recently detected in water of the Venice Lagoon, a vulnerable area continuously subjected to the income of anthropogenic chemicals. The lagoon is a relevant area for mollusc farming, including the Mediterranean mussels (Mytilus galloprovincialis) having an important economic and ecological role. Despite high levels of AS occurred in water of the Lagoon of Venice, no studies investigated the possible consequences of AS exposures on species inhabiting this ecosystem to date. For the first time, we applied a multidisciplinary approach to investigate the potential effects of the fragrance AS on Mediterranean mussels. To reach such a goal, bioaccumulation, cellular, biochemical, and molecular analyses (RNA-seq and microbiota characterization) were measured in mussels treated for 7 and 14 days with different AS Venice lagoon environmental levels (0.1 and 0.5 μg L⁻¹). Despite chemical investigations suggested low AS bioaccumulation capability, cellular and molecular analyses highlighted the disruption of several key cellular processes after the prolonged exposures to the high AS concentration. Among them, potential immunotoxicity and changes in transcriptional regulation of pathways involved in energy metabolism, stress response, apoptosis and cell death regulations have been observed. Conversely, exposure to the low AS concentration demonstrated weak transcriptional changes and transient increased representation of opportunistic pathogens, as Arcobacter genus and Vibrio aestuarianus. Summarizing, this study provides the first overview on the effects of AS on one of the most widely farmed mollusk species.

Ambient particles with aerodynamic diameter <0.1 μm (PM₀.₁) have been suggested to have significant health impact. However, studies on the association between long-term PM₀.₁ exposure and human blood lipid metabolism are still limited. This study was aimed to evaluate such association based on multiple lipid biomarkers and dyslipidemia indicators. We matched the 2006–2009 average PM₀.₁ concentration simulated using the neural-network model following the WRF-Chem model with the clinical and questionnaire data of 15,477 adults randomly recruited from 33 communities in Northeast China in 2009. After controlling for social demographic and behavior confounders, we assessed the association of PM₀.₁ concentration with multiple lipid biomarkers and dyslipidemia indicators using generalized linear mixed-effect models. Effect modification by various social demographic and behavior factors was examined. We found that each interquartile range increase in PM₀.₁ concentration was associated with a 5.75 (95% Confidence interval, 3.24–8.25) mg/dl and a 6.05 (2.85–9.25) mg/dl increase in the serum level of total cholesterol and LDL-C, respectively. This increment was also associated with an odds ratio of 1.25 (1.10–1.42) for overall dyslipidemias, 1.41 (1.16, 1.73) for hypercholesterolemia, and 1.90 (1.39, 2.61) for hyperbetalipoproteinemia. Additionally, we found generally greater effect estimates among the younger participants and those with lower income or with certain behaviors such as high-fat diet. The deleterious effect of long-term PM₀.₁ exposure on lipid metabolism may make it an important toxic chemical to be targeted by future preventive strategies.

This international scale study measured the prevalence of indoor microplastics (MPs) in deposited dust in 108 homes from 29 countries over a 1-month period. Dust borne MPs shape, colour, and length were determined using microscopy and the composition measured using μFTIR. Human health exposure and risk was assessed along with residential factors associated with MPs via a participant questionnaire. Samples were categorised according to each country's gross national income (GNI). Synthetic polymers dominated in low income (LI) (39%) and high income (HI) (46%) while natural fibres were the most prevalent in medium income (MI) (43%) countries. Composition and statistical analysis showed that the main sources of MPs and dust were predominantly from indoor sources. Across all GNI countries, greater vacuuming frequency was associated with lower MPs loading. High income country samples returned higher proportions of polyamides and polyester fibres, whereas in LI countries polyurethane was the most prominent MPs fibre. Exposure modelling showed infants (0–2 years) were exposed to the highest MPs dose through inhalation (4.5 × 10⁻⁵ ± 3 × 10⁻⁵) and ingestion (3.24 × 10⁻² ± 3.14 × 10⁻²) mg/kg-Bw/day. Health risk analysis of constituent monomers of polymers indicates cancer incidence was estimated at 4.1–8.7 per million persons across age groups. This study's analysis showed socio-economic factors and age were dominant variables in determining dose and associated health outcomes of MPs in household dust.

This systematic review and meta-analysis evaluates the most recent evidence to examine whether use of improved biomass cookstoves in households in low-middle income countries results in reduction in mean concentrations of carbon monoxide (CO) and particulate matter of size 2.5 μm (PM₂.₅) in the cooking area, as well as reduction in mean systolic (SBP) and diastolic blood pressure (DBP) of adults using the cookstoves when compared to adults who use traditional three stone fire or traditional biomass cookstoves.We searched databases of scientific and grey literature. We included studies if published between January 2012 and June 2021, reported impact of ICS interventions in non-pregnant adults in low/middle-income countries, and reported post-intervention results along with baseline of traditional cookstoves. Outcomes included 24- or 48-h averages of kitchen area PM₂.₅, CO, mean SBP and DBP. Meta-analyses estimated weighted mean differences between baseline and post-intervention values for all outcome measures.Eleven studies were included; ten contributed estimates for HAP and four for BP. Interventions lead to significant reductions in PM₂.₅ (−0.73 mg/m³, 95% CI: −1.33, −0.13), CO (−8.37 ppm, 95%CI: −13.20, −3.54) and SBP (−2.82 mmHg, 95% CI: −5.53, −0.11); and a non-significant reduction in DBP (−0.80 mmHg, 95%CI: −2.33, 0.73), when compared to baseline of traditional cookstoves. Except for DBP, greatest reductions in all outcomes came from standard combustion ICS with a chimney, compared to ICS without a chimney and advanced combustion ICS.Among the reviewed biomass stove types, ICS with a chimney feature resulted in greatest reductions in HAP and BP.

In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People’s Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM₂.₅ was a major contributor to COVID-19 cases in England, as an increase of 1 m³ in the long-term average of PM₂.₅ was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic.

Association between long-term exposure to ambient air pollution and obesity remains inconclusive, and the evidence from rural areas was limited. Thus, this study aimed to assess the association between ambient air pollution and obesity based on different anthropometric indices in Chinese rural adults, and further to compare the effect sizes of different air pollution types. A total of 38,824 participants (aged 18–79 years) were recruited from the Henan Rural Cohort Study. Logistic and multivariable linear regression model were used to examine the association between ambient air pollution exposure (including particulate matter with aerodynamic diameters ≤ 1.0 μm (PM₁), ≤2.5 μm (PM₂.₅), and ≤10 μm (PM₁₀), and nitrogen dioxide (NO₂)) and obesity as well as obese anthropometric indices (including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI)). The potential effect modifications were also examined. Positive associations were found between long-term exposure to PM₁, PM₂.₅, PM₁₀ and NO₂ and obesity regardless of how obesity was defined (false discovery rate (FDR) < 0.05). Moreover, BMI, WC, WHR, WHtR, BFP, and VFI displayed increased trends with PM₁, PM₂.₅, PM₁₀ and NO₂ concentrations increasing (all FDR<0.05). PM₁₀ had the largest effects on obesity among the four types of air pollution. The elderly, women, individuals with low level of education and income, and those who had high fat diet were more vulnerable to the adverse effects of air pollution. In addition, the results of the sensitivity analysis showed that those associations between ambient air pollution and obesity remained robust. These findings suggest that long-term exposure to ambient air pollutant (particularly PM₁₀) may be positively associated with obesity in Chinese rural adults, especially among the elderly, women, individuals with low education and income, as well as unhealthy lifestyles.

The urban nitrogen (N) and carbon (C) cycles are substantially influenced by human activity. Alterations to these cycles include increased inputs from fossil fuel combustion and fertilizer use. The leaf chemistry of urban trees can be used to distinguish between these different N and C sources. Here, we evaluated relationships between urban vegetation and different N and C sources in street and residential trees in the Salt Lake Valley, Utah. We tested three hypotheses: 1) unfertilized street trees on high traffic density roads will have higher leaf %N, more enriched δ¹⁵N and more depleted δ¹³C than unfertilized street trees on low traffic density roads; 2) trees in high income residential neighborhoods will have higher leaf %N, more depleted δ¹⁵N and more enriched δ¹³C than trees in lower income neighborhoods; and 3) unfertilized street trees will have lower leaf %N, more enriched δ¹⁵N and more depleted δ¹³C than fertilized residential trees. Leaf δ¹⁵N was more enriched near high traffic density roads for one study species. However, street tree δ¹⁵N and δ¹³C were largely influenced by vehicle emissions from primary and secondary roads within 1000 m radius rather than the immediately adjacent road. Leaf δ¹³C was correlated with neighborhood income, although this relationship may be the result of variations in irrigation practices rather than variations in C sources. Finally, unfertilized trees in downtown Salt Lake had lower leaf %N, more enriched δ¹⁵N and more depleted δ¹³C than fertilized trees. These results highlight that urban trees can serve as biomonitors of the environment. Moreover, they emphasize that roads can have large spatial footprints and that the leaf chemistry of urban vegetation may be influenced by the spatial patterns in roads and road densities at the landscape scale.

Air pollution contributes significantly to premature death in China. However, only a limited number of studies have identified the potential determinants of population exposure to PM2.5 from a socioeconomic perspective. This paper analyses the socioeconomic determinants of population exposure at the city level in China. We first estimated population exposure to PM2.5 by integrating high resolution spatial distribution maps of PM2.5 concentrations and population density, using data for 2013. Then, geographically weighted regression (GWR) modeling was undertaken to explore the strength and direction of relationships between the selected socioeconomic factors and population exposure. The results indicate that approximately 75% of the population of China lived in an area where PM2.5 concentrations were over 35 μg/m3 in 2013. From the GWR models, we found that the percentages for cities that showed a statistically significant relationship (p < 0.05) between population exposure and each of the six factors were: urbanization, 91.92%; industry share, 91.58%; construction level, 88.55%; urban expansion, 73.40%; income disparity, 64.98%; and private vehicles, 27.27%. The R-squared value for the six factors in the multivariable GWR model was 0.88, and all cities demonstrated a statistically significant relationship. More importantly, the association between the six factors and population exposure was found to be spatially heterogeneous at the local geographic level. Consideration of these six drivers of population exposure can help policy makers and epidemiologists to evaluate and reduce population exposure risks.

Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010–2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reflection of the burden associated with AT. The heat effect appeared at lag 0–1 days, with 19% (95% CI, 11–26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0–28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents’ per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.