Mortality analysis by neighbourhood in a city with high levels of industrial air pollution

Ports and their influence on local air pollution and public health: A global analysis

Despite the skyrocketing growth in recent decades of environmental studies on ports and shipping, their local health impacts remain largely under-researched. This article tackles this gap in research by statistically analyzing data on global shipping flows across nearly 5000 ports in 35 OECD countries between 2001 and 2018. The different traffic types, from containers to bulk and passengers, are analyzed jointly with data on natural conditions, air pollution, socio-economic indicators, and public health. The principal results show that port regions pollute more than non-port regions on average, while health impacts vary according to the size and specialization of the port region. Three types of port regions are clearly differentiated: industrial, intermediate, and metropolitan port regions.

Use of official municipal demographics for the estimation of mortality in cities suffering from heavy environmental pollution: Results of the first study on all the neighborhoods of Taranto from 2011 to 2020

BACKGROUND

In cities suffering from heavy environmental pressure or pollution, it is extremely important to rapidly access municipal demographics that can be used as indicators of population health status. Among those, mortality rates represent the most reliable data as they are officially retained and available to municipality with high level of details, thus allowing epidemiological comparison between different neighborhoods of the city across several years. Our study was aimed at validating and propose as universally applicable approach the use of municipal demographics as first-line tool to rapidly assess population health and drive health policies or urban planning in cities characterized by heavy environmental pressure. The case study of Taranto has been chosen due to the presence of the biggest European steel plant since 1960s resulting in heavy burden on environment and population health.

METHODS

We have performed an ecological study on general mortality data due to all causes, specific by gender, age groups and disaggregated at sub-municipal level (highest data granularity) into neighborhoods from 2011 to 2020 by using official demographics related to all people living in Taranto available at General Registry Office of the municipality. A preliminary analysis comparing data available at Municipality and those provided by the Italian National Institute of Statistics (ISTAT) was performed and confirmed the high level of reliability of the municipal source of data. For comparative analyses, we used Regional demographics and mortality from ISTAT. Indirect age-standardized mortality ratios (SMR; CI 90% and 95%), specific for gender and neighborhoods, were calculated in reference to the city of Taranto and Apulia Region; direct age-standardized and neighborhoods mortality rates were computed on city population.

RESULTS

The city of Taranto shows relevant inequalities in terms of mortality between the northern neighborhoods, closest to the industrial area (Paolo VI, Tamburi and Città Vecchia-Borgo), with excess mortality highlighted across 10 years described by SMRs always higher than those of the entire Apulia region, with peaks exceeding 50% between 2015 and 2017 both in women and men. The significant excesses of mortality have increased from 2011 to 2020 and progressively extended across several neighborhoods of Taranto city. Compared to the Apulia region, in the 3 Northern neighborhoods of the city (Paolo VI, Tamburi and Città Vecchia-Borgo) a total of 1020 excess deaths were recorded from 2011 to 2019 in both males and females (showing statistical significance), with a peak of 68% mortality excess in 2019 for men living in Paolo VI district.

CONCLUSION

The use of official mortality data allows a timely, reliable and costless assessment of population health in cities heavily impacted by environmental pollution like Taranto.

First Attempt to Couple Proteomics with the AhR Reporter Gene Bioassay in Soil Pollution Monitoring and Assessment

A topsoil sample obtained from a highly industrialized area (Taranto, Italy) was tested on the DR-CALUX^® cell line and the exposed cells processed with proteomic and bioinformatics analyses. The presence of polyhalogenated compounds in the topsoil extracts was confirmed by GC-MS/MS analysis. Proteomic analysis of the cells exposed to the topsoil extracts identified 43 differential proteins. Enrichment analysis highlighted biological processes, such as the cellular response to a chemical stimulus, stress, and inorganic substances; regulation of translation; regulation of apoptotic process; and the response to organonitrogen compounds in light of particular drugs and compounds, extrapolated by bioinformatics all linked to the identified protein modifications. Our results confirm and reflect the complex epidemiological situation occurring among Taranto inhabitants and underline the need to further investigate the presence and sources of inferred chemicals in soils. The combination of bioassays and proteomics reveals a more complex scenario of chemicals able to affect cellular pathways and leading to toxicities rather than those identified by only bioassays and related chemical analysis. This combined approach turns out to be a promising tool for soil risk assessment and deserves further investigation and developments for soil monitoring and risk assessment.

Environmental assessment of interventions to restrain the impact of industrial pollution using a quasi-experimental design: limitations of the interventions and recommendations for public health policy

Background

In an industrial area, the asymmetry between the weights of the economic interests compared to the public-health needs can determine which interests are represented in decision-making processes. This might lead to partial interventions, whose impacts are not always evaluated. This study focuses on two interventions implemented in Taranto, Italy, a city hosting one of the largest steel plants in Europe. The first intervention deals with measures industrial plants must implement by law to reduce emissions during so called “wind days” in order to reduce PM₁₀ and benzo [a] pyrene concentrations. The second one is a warning to the population with recommendations to aerate indoor spaces from 12 pm to 6 pm, when pollutant concentrations are believed to be lower.

Methods

To analyse the impact of the first intervention, we analysed monthly PM₁₀ data in the period 2009–2016 from two monitoring stations and conducted an interrupted-time-series analysis. Coefficients of time-based covariates are estimated in the regression model. To minimise potential confounding, monthly concentrations of PM₁₀ in a neighbourhood 13 km away from the steel plant were used as a control series. To evaluate the second intervention, hourly concentrations of PM₁₀, SO₂ and polycyclic-aromatic-hydrocarbons (PAHs) were analysed.

Results

PM₁₀ concentrations in the intervention neighbourhood showed a peak just a few months before the introduction of the law. When compared to the control series, PM₁₀ concentrations were constantly higher throughout the entire study period. After the intervention, there was a reduction in the difference between the two time-series (− 25.6%). During “wind days” results suggested no reduction in concentrations of air pollutants from 12 pm to 18 pm.

Conclusion

Results of our study suggest revising the warning to the population. Furthermore, they evidence that in complex highly industrialised areas, air quality interventions cannot focus on only a single pollutant, but rather should consider the complex relationships between the different contaminants. Environmental interventions should be reviewed periodically, particularly when they have implications for social constraints. While the results of our study can be related only to the specific situation reported in the article, the methodology applied might be useful for the environmental management in industrial areas with similar features.

Occurrence and spatial distribution of dioxin and dioxin-like compounds in topsoil of Taranto (Apulia, Italy) by GC-MS analysis and DR-CALUX® bioassay

The aim of the present study was to assess the occurrence and spatial distribution of PCDD/Fs and dioxin-like compounds in topsoils of Taranto (Apulia Region), one of the most heavily industrialized and contaminated area of Southern Italy. A combined approach of chemical analysis by GC-MS/MS and AhR reporter gene bioassay was applied in a subset of topsoil samples (n = 20) collected in 2017-18 from ten sites embracing three levels of risk (from high to low) in the framework of a large survey inside Taranto municipality. TCDD-BEQs and GC-MS/MS TEQ_WHO and TEQ_THEORETICAL revealed a decreasing trend with the distance from main industrial settings and landfill areas. A strong correlation between TCDD-BEQs and TEQ_WHO values (R² = 0.85) and TEQ_THEORETICAL (R² = 0.88) was also found. In 3 out of 10 topsoil investigated, BEQs and TEQ_{WHO/THEORETICAL} resulted above Italian National Regulatory Limits for ∑PCDD/Fs in green, private and recreational used soils (10 ng TEQ/kg d.w. D.Lgs 152/2006) and for ∑PCDD/F/dl-PCBs in agricultural and farming soil (6 ng TEQ/kg d.w. D.M. 46/2019). GC-MS/MS pattern revealed the highest prevalence of dl-PCBs in 6 out of 10 sites, followed by PCDFs and PCDDs. Those sites are all located in proximity of main industrial steel and iron ore sinter plant, steel plant's landfills and illegal dumping sites. An update on occurrence and spatial distribution of PCDD/Fs and dl-PCBs contamination of Taranto urban soils was obtained and the DR-CALUX® bioassay was further recommended as a suitable screening tool for environmental and human risk assessment.

Particle-Bound PAHs and Elements in a Highly Industrialized City in Southern Italy: PM2.5 Chemical Characterization and Source Apportionment after the Implementation of Governmental Measures for Air Pollution Mitigation and Control

The present study was aimed at determining airborne concentrations of PAHs, Nitro-/Oxy-PAHs and elements in industrial and urban areas of Taranto, a site of environmental risk in Southern Italy, after the issue of strategic measures for air pollution mitigation and control by the Italian Environment Ministry in 2012. A PM_2.5 sampling campaign was carried out from 9 to 28 December 2014 at eight receptor sites, two placed in the urban settlement and five included in the high spatial resolution fence monitoring network of the biggest European steel plant. The integration of collected data with meteorological parameters and source apportionment analysis by Positive Matrix Factorization and bivariate polar plots allowed to discriminate among emission sources and estimate their contributions. Evidence on the effect of distinct processes (homogenization, sintering) occurring inside the steel plant on airborne concentrations of PAHs and selected elements was provided. The impact of emissions from the steel plant “core” on the surrounding area was observed at receptor sites downwind to it. Moreover, the extent of the effectiveness of mitigation measures, partially applied at the moment of study’s beginning, was demonstrated by mean and peak pollutant concentrations at all receptor sites up to one order of magnitude lower than those documented prior to 2012.

Characteristics of Polycyclic Aromatic Hydrocarbons (PAHs) and Common Air Pollutants at Wajima, a Remote Background Site in Japan

Background: Background sites are mainly affected by long-range-transported air pollutants, resulting in potential adverse effects on local atmospheric environments. A 4–5 year observational study was conducted to illustrate the air pollution profile at the Kanazawa University Wajima air monitoring station (KUWAMS), an ideal remote background site in Japan. Methods: Nine polycyclic aromatic hydrocarbons (PAHs) in the particulate phase and various air pollutants were continuously monitored for 4–5 years. Diagnostic ratios of PAHs and back-trajectory analysis were applied to trace the possible sources of the air pollutants collected at the sampling site. Results: The atmospheric concentration of PAHs in the atmosphere at the site decreased from 2014 to 2019, benefit from the predominant air pollution control policy in China and Japan. Common air pollutants including sulfur dioxide (SO₂), nitrogen oxides (NO_x), ozone, methane (CH₄), and non-methane hydrocarbon (NMHC) were detected in low concentrations from 2016 to 2019, while ozone (O₃) and particulate matter (PM_2.5, PM with a diameter less than 2.5 μm) were present in high levels that exceeded the Japanese standards. Most air pollutants peaked in spring and showed evident diurnal variations in spring and summer. Conclusions: This is the first study to clarify the atmospheric behaviors of multiple air pollutants at a background site in Japan. Significant external air pollutant impact and unneglectable air pollution were demonstrated at KUWAMS, indicating the importance of studying atmospheric pollution at remote sites.

Industrial air pollution and mortality in the Taranto area, Southern Italy: A difference-in-differences approach

BACKGROUND

A large steel plant close to the urban area of Taranto (Italy) has been operating since the sixties. Several studies conducted in the past reported an excess of mortality and morbidity from various diseases at the town level, possibly due to air pollution from the plant. However, the relationship between air pollutants emitted from the industry and adverse health outcomes has been controversial. We applied a variant of the "difference-in-differences" (DID) approach to examine the relationship between temporal changes in exposure to industrial PM₁₀ from the plant and changes in cause-specific mortality rates at area unit level.

METHODS

We examined a dynamic cohort of all subjects (321,356 individuals) resident in the Taranto area in 1998-2010 and followed them up for mortality till 2014. In this work, we included only deaths occurring on 2008-2014. We observed a total of 15,303 natural deaths in the cohort and age-specific annual death rates were computed for each area unit (11 areas in total). PM₁₀ and NO₂ concentrations measured at air quality monitoring stations and the results of a dispersion model were used to estimate annual average population weighted exposures to PM₁₀ of industrial origin for each year, area unit and age class. Changes in exposures and in mortality were analyzed using Poisson regression.

RESULTS

We estimated an increased risk in natural mortality (1.86%, 95% confidence interval [CI]: -0.06, 3.83%) per 1 μg/m³ annual change of industrial PM₁₀, mainly driven by respiratory causes (8.74%, 95% CI: 1.50, 16.51%). The associations were statistically significant only in the elderly (65+ years).

CONCLUSIONS

The DID approach is intuitively simple and reduces confounding by design. Under the multiple assumptions of this approach, the study indicates an effect of industrial PM₁₀ on natural mortality, especially in the elderly population.

Regional Inequalities in Lung Cancer Mortality in Belgium at the Beginning of the 21st Century: The Contribution of Individual and Area-Level Socioeconomic Status and Industrial Exposure

Being a highly industrialized country with one of the highest male lung cancer mortality rates in Europe, Belgium is an interesting study area for lung cancer research. This study investigates geographical patterns in lung cancer mortality in Belgium. More specifically it probes into the contribution of individual as well as area-level characteristics to (sub-district patterns in) lung cancer mortality. Data from the 2001 census linked to register data from 2001-2011 are used, selecting all Belgian inhabitants aged 65+ at time of the census. Individual characteristics include education, housing status and home ownership. Urbanicity, unemployment rate, the percentage employed in mining and the percentage employed in other high-risk industries are included as sub-district characteristics. Regional variation in lung cancer mortality at sub-district level is estimated using directly age-standardized mortality rates. The association between lung cancer mortality and individual and area characteristics, and their impact on the variation of sub-district level is estimated using multilevel Poisson models. Significant sub-district variations in lung cancer mortality are observed. Individual characteristics explain a small share of this variation, while a large share is explained by sub-district characteristics. Individuals with a low socioeconomic status experience a higher lung cancer mortality risk. Among women, an association with lung cancer mortality is found for the sub-district characteristics urbanicity and unemployment rate, while for men lung cancer mortality was associated with the percentage employed in mining. Not just individual characteristics, but also area characteristics are thus important determinants of (regional differences in) lung cancer mortality.

Land use regression models for crustal and traffic-related PM2.5 constituents in four areas of the SAPALDIA study

Many studies have documented adverse health effects of long-term exposure to fine particulate matter (PM2.5), but there is still limited knowledge regarding the causal relationship between specific sources of PM2.5 and such health effects. The spatial variability of PM2.5 constituents and sources, as a exposure assessment strategy for investigating source contributions to health effects, has been little explored so far. Between 2011 and 2012, three measurement campaigns of PM and nitrogen dioxide (NO2) were performed in 80 sites across four areas of the Swiss Study on Air Pollution and Lung and heart Diseases in Adults (SAPALDIA). Reflectance analysis and energy dispersive X-ray fluorescence (XRF) were performed on PM2.5 filter samples to estimate light absorbance and trace element concentrations, respectively. Three air pollution source factors were identified using principal-component factor analysis: vehicular, crustal, and long-range transport. Land use regression (LUR) models were developed for temporally-adjusted scores of each factor, combining the four study areas. Model performance was assessed using two cross-validation methods. Model explained variance was high for the vehicular factor (R(2)=0.76), moderate for the crustal factor (R(2)=0.46), and low for the long-range transport factor (R(2)=0.19). The cross-validation methods suggested that models for the vehicular and crustal factors moderately accounted for both the between and within-area variability, and therefore can be applied to the four study areas to estimate long-term exposures within the SAPALDIA study population. The combination of source apportionment techniques and LUR modelling may help in identifying air pollution sources and disentangling their contribution to observed health effects in epidemiologic studies.

Deprivation and suicide mortality across 424 neighborhoods in Seoul, South Korea: a Bayesian spatial analysis

OBJECTIVES

A neighborhood-level analysis of mortality from suicide would be informative in developing targeted approaches to reducing suicide. This study aims to examine the association of community characteristics with suicide in the 424 neighborhoods of Seoul, South Korea.

METHODS

Neighborhood-level mortality and population data (2005-2011) were obtained to calculate age-standardized suicide rates. Eight community characteristics and their associated deprivation index were employed as determinants of suicide rates. The Bayesian hierarchical model with mixed effects for neighborhoods was used to fit age-standardized suicide rates and other covariates with consideration of spatial correlations.

RESULTS

Suicide rates for 424 neighborhoods were between 7.32 and 71.09 per 100,000. Ninety-nine percent of 424 neighborhoods recorded greater suicide rates than the Organization for Economic Cooperation and Development member countries' average. A stepwise relationship between area deprivation and suicide was found. Neighborhood-level indicators for lack of social support (residents living alone and the divorced or separated) and socioeconomic disadvantages (low educational attainment) were positively associated with suicide mortality after controlling for other covariates.

CONCLUSIONS

Finding from this study could be used to identify priority areas and to develop community-based programs for preventing suicide in Seoul, South Korea.

Short-term airborne particulate matter exposure alters the epigenetic landscape of human genes associated with the mitogen-activated protein kinase network: a cross-sectional study

BACKGROUND

Exposure to air particulate matter is known to elevate blood biomarkers of inflammation and to increase cardiopulmonary morbidity and mortality. Major components of airborne particulate matter typically include black carbon from traffic and sulfates from coal-burning power plants. DNA methylation is thought to be sensitive to these environmental toxins and possibly mediate environmental effects on clinical outcomes via regulation of gene networks. The underlying mechanisms may include epigenetic modulation of major inflammatory pathways, yet the details remain unclear.

METHODS

We sought to elucidate how short-term exposure to air pollution components, singly and/or in combination, alter blood DNA methylation in certain inflammation-associated gene networks, MAPK and NF-κB, which may transmit the environmental signal(s) and influence the inflammatory pathway in vivo. To this end, we utilized a custom-integrated workflow-molecular processing, pollution surveillance, biostatical analysis, and bioinformatic visualization-to map novel human (epi)gene pathway-environment interactions.

RESULTS

Specifically, out of 84 MAPK pathway genes considered, we identified 11 whose DNA methylation status was highly associated with black carbon exposure, after adjusting for potential confounders-age, sulfate exposure, smoking, blood cell composition, and blood pressure. Moreover, after adjusting for these confounders, multi-pollutant analysis of synergistic DNA methylations significantly associated with sulfate and BC exposures yielded 14 MAPK genes. No associations were found with the NF-κB pathway.

CONCLUSION

Exposure to short-term air pollution components thus resulted in quantifiable epigenetic changes in the promoter areas of MAPK pathway genes. Bioinformatic mapping of single- vs. multi-exposure-associated epigenetic changes suggests that these alterations might affect biological pathways in nuanced ways that are not simply additive or fully predictable via individual-level exposure assessments.