Proximity to wood factories and hospitalizations for respiratory diseases in children

Residential exposure to air pollution and incidence of leukaemia in the industrial area of Viadana, Northern Italy

BACKGROUND

Exposure to air pollution has been proposed as one of the potential risk factors for leukaemia. Work-related formaldehyde exposure is suspected to cause leukaemia.

METHODS

We conducted a nested register-based case-control study on leukaemia incidence in the Viadana district, an industrial area for particleboard production in Northern Italy. We recruited 115 cases and 496 controls, frequency-matched by age, between 1999 and 2014. We assigned estimated exposures to particulate matter (PM10, PM2.5), nitrogen dioxide (NO2), and formaldehyde at residential addresses, averaged over the susceptibility window 3rd to 10th year prior to the index date. We considered potential confounding by sex, age, nationality, socio-economic status, occupational exposures to benzene and formaldehyde, and prior cancer diagnoses.

RESULTS

There was no association of exposures to PM10, PM2.5, and NO2 with leukaemia incidence. However, an indication of increased risk emerged for formaldehyde, despite wide statistical uncertainty (OR 1.46, 95%CI 0.65-3.25 per IQR-difference of 1.2 μg/m3). Estimated associations for formaldehyde were higher for acute (OR 2.07, 95%CI 0.70-6.12) and myeloid subtypes (OR 1.79, 95%CI 0.64-5.01), and in the 4-km buffer around the industrial facilities (OR 2.78, 95%CI 0.48-16.13), although they remained uncertain.

CONCLUSIONS

This was the first study investigating the link between ambient formaldehyde exposure and leukaemia incidence in the general population. The evidence presented suggests an association, although it remains inconclusive, and a potential significance of emissions related to industrial activities in the district. Further research is warranted in larger populations incorporating data on other potential risk factors.

Estimation of Urban Housing Vacancy Based on Daytime Housing Exterior Images—A Case Study of Guangzhou in China

The traditional methods of estimating housing vacancies rarely use daytime housing exterior images to estimate housing vacancy rates (HVR). In view of this, this study proposed the idea and method of estimating urban housing vacancies based on daytime housing exterior images, taking Guangzhou, China as a case study. Considering residential quarters as the basic evaluation unit, the spatial pattern and its influencing factors were studied by using average nearest neighbor analysis, kernel density estimation, spatial autocorrelation analysis, and geodetector. The results show that: (1) The urban housing vacancy rate can be estimated by the method of daytime housing exterior images, which has the advantage of smaller research scale, simple and easy operation, short time consumption, and less difficulty in data acquisition. (2) Overall, the housing vacancy rate in Guangzhou is low in the core area and urban district, followed by suburban and higher in the outer suburb, showing a spatial pattern of increasing core area–urban district–suburban–outer suburb. Additionally, it has obvious spatial agglomeration characteristics, with low–low value clustered in the inner circle and high–high value clustered in the outer suburb. (3) The residential quarters with low vacancy rates (<5%) are distributed in the core area, showing a “dual-core” pattern, while residential quarters with high vacancy rates (>50%) are distributed in the outer suburb in a multi-core point pattern, both of which have clustering characteristics. (4) The results of the factor detector show that all seven influencing factors have an impact on the housing vacancy rate, but the degree of impact is different; the distance from CBD (Central Business District) has the strongest influence, while subway accessibility has the weakest influence. This study provides new ideas and methods for current research on urban housing vacancies, which can not only provide a reference for residents to purchase houses rationally, but also provide a decision-making basis for housing planning and policy formulation in megacities.

Relationship between Urban Floating Population Distribution and Livability Environment: Evidence from Guangzhou’s Urban District, China

The livability environment is an important aspect of urban sustainable development. The floating population refers to people without local hukou (also called ‘non-hukou migrants’). The floating population distribution is influenced by livability environment, but few studies have investigated this relationship. Especially, the influence of social environment on floating population distribution is rarely studied. Therefore, we study 1054 communities in Guangzhou’s urban district to explore the relationship between livability environment and floating population distribution. The purpose of this article is to study how livability environment affects floating population distribution. We develop a conceptual framework of livability environment, which consists of physical environment, social environment and life convenience. A cross-sectional dataset of the impact of livability environment on the floating population distribution is developed covering the proportion of floating population in the community as the dependent variable, eight factors of livability environment as the explanatory variables, and two factors of architectural characteristics and one factor of location characteristics as the control variables. We use spatial regression models to explore the degree of influence and direction of physical environment, social environment and life convenience on the floating population distribution in livability environment. The results show that the spatial error model is more effective than ordinary least squares and spatial lag model models. The five factors of the livability environment have statistical significance regarding floating population distribution, including four social environment factors (proportion of middle- and high-class occupation population, proportion of highly educated people in the population, proportion of rental households, and unemployment rate) and regarding life convenience factors (work and shopping convenience). The conclusion has value for understanding how the social environment affects the residential choice of the floating population. This study will help city administrators reasonably guide the residential pattern of the floating population and formulate reasonable management policies, thereby improving the city’s livability, attractiveness and sustainable development.

Spatial variability of nitrogen dioxide and formaldehyde and residential exposure of children in the industrial area of Viadana, Northern Italy

Chipboard production is a source of ambient air pollution. We assessed the spatial variability of outdoor pollutants and residential exposure of children living in proximity to the largest chipboard industry in Italy and evaluated the reliability of exposure estimates obtained from a number of available models. We obtained passive sampling data on NO₂ and formaldehyde collected by the Environmental Protection Agency of Lombardy region at 25 sites in the municipality of Viadana during 10 weeks (2017-2018) and compared NO₂ measurements with average weekly concentrations from continuous monitors. We compared interpolated NO₂ and formaldehyde surfaces with previous maps for 2010. We assessed the relationship between residential proximity to the industry and pollutant exposures assigned using these maps, as well as other available countrywide/continental models based on routine data on NO₂, PM₁₀, and PM_2.5. The correlation between NO₂ concentrations from continuous and passive sampling was high (Pearson's r = 0.89), although passive sampling underestimated NO₂ especially during winter. For both 2010 and 2017-2018, we observed higher NO₂ and formaldehyde concentrations in the south of Viadana, with hot-spots in proximity to the industry. PM₁₀ and PM_2.5 exposures were higher for children at < 1 km compared to the children living at > 3.5 km to the industry, whereas NO₂ exposure was higher at 1-1.7 km to the industry. Road and population densities were also higher close to the industry. Findings from a variety of exposure models suggest that children living in proximity to the chipboard industry in Viadana are more exposed to air pollution and that exposure gradients are relatively stable over time.

Combinations of Epidemiological and Experimental Studies in Air Pollution Research: A Narrative Review

Scientific literature is evolving to include more systematic reviews that encompass epidemiological and experimental papers so that the whole picture can be examined. The aim of this narrative review is to bridge that gap by combining epidemiological and experimental studies based on the same setting: Examples of Bitterfeld, Utah Valley, Beijing Olympic Games, and Viadana. This review looks at four examples that incorporate multiple epidemiological and experimental papers about air pollution exposure and health effects. The Bitterfeld (spatial) and Utah Valley (temporal) examples showed that particle composition causes the biggest difference in lung injury. In Beijing, a temporal difference of before/after and during the Olympics showed that traffic and industry air pollution-related health effects like lung cancer and cardiovascular disease could be reduced by improvement of air quality. The Viadana example showed a spatial difference in respiratory injury caused by particle composition and interactions with genotoxicity. Combining experimental and epidemiological methods gives a more in-depth look into the whole picture of exposure and health effects. Our review exemplifies the strength of this strategy and encourages further use of it.

Review of the effect of air pollution exposure from industrial point sources on asthma-related effects in childhood

We reviewed epidemiologic studies of the association between exposure to air pollution from industries and asthma-related outcomes in childhood. We searched bibliographic databases and reference lists of relevant articles to identify studies examining the association between children's exposure to air pollution from industrial point-sources and asthma-related outcomes, including asthma, asthma-like symptoms, wheezing, and bronchiolitis. We extracted key characteristics of each study and when appropriate we performed a random-effects meta-analysis of results and quantified heterogeneity (I ²). Thirty-six studies were included in this review. Meta-analysis was generally not possible and limited to a few studies because of substantial variation across design characteristics and methodologies. In case-crossover studies using administrative health data, pooled odds ratio (OR) of hospitalization for asthma and bronchiolitis in children <5 years were 1.02 [95% confidence intervals (CI): 0.96, 1.08; I ² = 56%] and 1.01 (95% CI: 0.97, 1.05; I ² = 64%) per 10 ppb increase in the daily mean and hourly maximum concentration of sulfur dioxide (SO₂), respectively. For PM_2.5, pooled ORs were 1.02 (95% CI: 0.93, 1.10; I ² = 56%) and 1.01 (95% CI: 0.98, 1.03 I ² = 33%) per 10 μg/m³ increment in the daily mean and hourly maximum concentration. In cross-sectional studies using questionnaires, pooled ORs for the prevalence of asthma and wheezing in relation to residential proximity to industry were 1.98 (95% CI: 0.87, 3.09; I ² =71%) and 1.33 (95% CI: 0.86, 1.79; I ²= 65%), respectively. In conclusion, this review showed substantial heterogeneity across study designs and methods. Meta-analysis results suggested no evidence of an association for short-term asthma-related effects and an indication for long-term effects, but heterogeneity between results and limitations in terms of design and exposure assessment preclude drawing definite conclusions. Further well-conducted studies making use of a longitudinal design and of refined exposure assessment methods are needed to improve risk estimates.

A population-based birth cohort study of the association between childhood-onset asthma and exposure to industrial air pollutant emissions

BACKGROUND

Studies of the association between air pollution and asthma onset have mostly focused on urban and traffic-related air pollution. We investigated the associations between exposure to industrial emissions and childhood-onset asthma in a population-based birth cohort in Quebec, Canada, 2002-2011.

METHODS

The cohort was built from administrative health databases. We developed separately for PM_2.5 and SO₂ different metrics representing children's time-varying residential exposure to industrial emissions: 1) yearly number of tons of air pollutant emitted by industries located within 2.5 km of the residence; 2) distance to the nearest "major emitter" (≥100 tons) of either PM_2.5 and SO₂ within 7.5 km of the residence, and; 3) tons of air pollutant emitted by the nearest "major emitter" within 7.5 km, weighted by the inverse of the distance and the percentage of time that the residence was downwind. To handle the large number of zeros (i.e., children unexposed) we decomposed the exposure variable into two covariates simultaneously included in the regression model: a binary indicator of exposure and a continuous exposure variable centered at the mean value among exposed children. We performed Cox models using age as the time axis, adjusted for gender, material and social deprivation and calendar year. We indirectly adjusted for unmeasured secondhand smoke.

RESULTS

The cohort included 722,667 children and 66,559 incident cases of asthma. Across the different exposure metrics, mean percentage changes in the risk of asthma onset in children exposed to the mean relative to those unexposed ranged from 4.5% (95% CI: 2.8, 6.3%) to 10.6% (95% CI: 6.2, 15.2%) for PM_2.5 and, from 1.1% (95% CI: -0.1, 3.3%) to 8.9% (95% CI: 7.1, 11.1%) for SO₂. Indirect adjustment for secondhand smoke did not substantially affect the associations. In children exposed, the risk of asthma onset increased with the magnitude of the exposure for all metrics, except the distance to the nearest major emitter of SO₂.

CONCLUSIONS

In this population-based birth cohort, residential exposure to industrial air pollutant emissions was associated with childhood-onset asthma. Additional studies with improved models for estimating exposure to industrial point-sources are needed to further support the observed associations.

Estimating the Causal Impact of Proximity to Gold and Copper Mines on Respiratory Diseases in Chilean Children: An Application of Targeted Maximum Likelihood Estimation

In a town located in a desert area of Northern Chile, gold and copper open-pit mining is carried out involving explosive processes. These processes are associated with increased dust exposure, which might affect children's respiratory health. Therefore, we aimed to quantify the causal attributable risk of living close to the mines on asthma or allergic rhinoconjunctivitis risk burden in children. Data on the prevalence of respiratory diseases and potential confounders were available from a cross-sectional survey carried out in 2009 among 288 (response: 69 % ) children living in the community. The proximity of the children's home addresses to the local gold and copper mine was calculated using geographical positioning systems. We applied targeted maximum likelihood estimation to obtain the causal attributable risk (CAR) for asthma, rhinoconjunctivitis and both outcomes combined. Children living more than the first quartile away from the mines were used as the unexposed group. Based on the estimated CAR, a hypothetical intervention in which all children lived at least one quartile away from the copper mine would decrease the risk of rhinoconjunctivitis by 4.7 percentage points (CAR: - 4.7 ; 95 % confidence interval ( 95 % CI): - 8.4 ; - 0.11 ); and 4.2 percentage points (CAR: - 4.2 ; 95 % CI: - 7.9 ; - 0.05 ) for both outcomes combined. Overall, our results suggest that a hypothetical intervention intended to increase the distance between the place of residence of the highest exposed children would reduce the prevalence of respiratory disease in the community by around four percentage points. This approach could help local policymakers in the development of efficient public health strategies.

A score for measuring health risk perception in environmental surveys

BACKGROUND

In environmental surveys, risk perception may be a source of bias when information on health outcomes is reported using questionnaires. Using the data from a survey carried out in the largest chipboard industrial district in Italy (Viadana, Mantova), we devised a score of health risk perception and described its determinants in an adult population.

METHODS

In 2006, 3697 parents of children were administered a questionnaire that included ratings on 7 environmental issues. Items dimensionality was studied by factor analysis. After testing equidistance across response options by homogeneity analysis, a risk perception score was devised by summing up item ratings.

RESULTS

Factor analysis identified one latent factor, which we interpreted as health risk perception, that explained 65.4% of the variance of five items retained after scaling. The scale (range 0-10, mean ± SD 9.3 ± 1.9) had a good internal consistency (Cronbach's alpha 0.87). Most subjects (80.6%) expressed maximum risk perception (score = 10). Italian mothers showed significantly higher risk perception than foreign fathers. Risk perception was higher for parents of young children, and for older parents with a higher education, than for their counterparts. Actual distance to major roads was not associated with the score, while self-reported intense traffic and frequent air refreshing at home predicted higher risk perception.

CONCLUSIONS

When investigating health effects of environmental hazards using questionnaires, care should be taken to reduce the possibility of awareness bias at the stage of study planning and data analysis. Including appropriate items in study questionnaires can be useful to derive a measure of health risk perception, which can help to identify confounding of association estimates by risk perception.

Outdoor formaldehyde and NO2 exposures and markers of genotoxicity in children living near chipboard industries

BACKGROUND

Industrial air pollution is a public health hazard. Previous evidence documented increased respiratory symptoms and hospitalizations in children who live near the factories in the largest chipboard manufacturing district in Italy (Viadana).

OBJECTIVES

We evaluated the association of outdoor exposure to formaldehyde and nitrogen dioxide (NO2) with markers of early genotoxic damage in oral mucosa cells of randomly selected children (6-12 years of age) living in Viadana.

METHODS

In 2010-2011, DNA strand breaks and nuclear abnormalities were evaluated in exfoliated buccal cells by the comet and micronucleus assays, respectively, and formaldehyde and NO2 were monitored by passive sampling. Annual exposure estimates to pollutants were assigned to children's houses by spatial interpolation.

RESULTS

Of 656 children, 413 (63%) participated. Children living near (< 2 km) the chipboard industries had the highest average exposure to formaldehyde and NO2 (p < 0.001). A 1-SD increase in formaldehyde (0.20 μg/m(3)) was associated with a 0.13% (95% CI: 0.03, 0.22%) higher comet tail intensity, a 0.007 (95% CI: 0.001, 0.012) higher tail moment, and a 12% relative increase [relative risk (RR) = 1.12; 95% CI: 1.02, 1.23] in nuclear buds. A 1-SD NO2 increase (2.13 μg/m(3)) was associated with a 0.13% (95% CI: 0.07, 0.19%) increase in binucleated cells and a 16% relative increase (RR = 1.16; 95% CI: 1.06, 1.26) in nuclear buds.

CONCLUSIONS

Exposure to pollutants was associated with markers of genotoxicity in exfoliated buccal cells of children living in a region with chipboard industries. These findings, combined with previously reported associations between chipboard industrial activities and respiratory outcomes in children, add to concerns about potential adverse effects of industry-related exposures in the Viadana district.

Spatial analysis of binary health indicators with local smoothing techniques The Viadana study

INTRODUCTION

When pollution data from a monitoring network is not available, mapping the spatial distribution of disease can be useful to identify populations at risk and to suggest a potential role for suspected emission sources. We aimed at obtaining a continuous spatial representation of the prevalence of symptoms that are potentially associated with the exposure to the pollutants emitted from the wood factories in the children who live in the district of Viadana (Northern Italy).

METHODS

In 2006, all the parents of the children aged 3-14 years residing in the Viadana district (n = 3854), filled in a questionnaire on respiratory symptoms, irritation symptoms of the eyes and skin, use of health services. The children's residential addresses were also collected and geocoded. Generalized additive models and local weighted regression (LOWESS) were used to estimate the distribution of the symptoms, to test for spatial trends of the symptoms' prevalence and to control for potential confounders. Permutation tests were used to identify the areas of significantly increased risk ("hot spots").

RESULTS

The prevalence of respiratory symptoms, eye symptoms and the use of health services showed a statistically significant spatial variation (p < 0.05), but skin symptoms did not. Symptoms' prevalence was lower in the northern part of the district, where no wood factories were present, and it was higher in the southern part, where the two big chipboard industries were located. Hot spots were identified fairly near to one of the two chipboard industries in the district.

CONCLUSIONS

The north-to-south trend in the prevalence of respiratory and eye symptoms, but not of skin symptoms, as well as the location of hot spots, are consistent with the potential exposure to air pollutants both emitted by the wood factories and related to traffic. In these "high risk areas" monitoring of pollution and preventive actions are clearly needed.