Risk of respiratory cancer around a sewage plant in Prato, Italy

Lung Cancer Risk and Residence in the Neighborhood of a Sewage Plant in Italy. A Case-Control Study

Aims and background

Environmental pollution originating in sewage and industrial plants can be associated with lung cancer risk, as ecological and case-control studies have indicated. In the present study, the association between lung cancer occurrence and residence near a sewage plant in Prato (Italy) was investigated. A previous geographic study in the same area had shown an increasing trend of lung cancer mortality and incidence with propinquity to the plant.

Methods

A case-control study was carried out in the male population of Prato. Incident cases in the period 1987–1997 were identified from the Tuscan Cancer Registry (no. 918). Controls were randomly extracted from the Registry Office of the Municipality of Prato (no. 1852). For all subjects, the residential history was reconstructed. A weighted average distance from the plant was computed and used as a proxy variable of exposure. Two analyses were performed: on the whole data set and on a subset of subjects for whom information on tobacco exposure and education was obtained through a postal questionnaire (response rate, 41.1%). Logistic regression models were applied to estimate odds ratios and 95% CI.

Results

Both analyses showed a significantly elevated lung cancer risk for subjects living within 1.5 km (ORwhole = 1.56, 1.06–2.28; ORsubset = 2.28, 1.06–4.86) and suggested a risk increase with a decrease of weighted average distance from the plant.

Conclusions

The findings highlight a possible role, in lung cancer occurrence, for environmental pollution spread from the plant. Due to drawbacks of the study, further analyses are needed to evidence a noncontroversial etiological conclusion. When environmental data are not available, results of epidemiological studies using residential histories may be useful in preventive policies regarding point source emissions. Free full text available at www.tumorionline.it

Risk of neuroblastoma and residential proximity to industrial and urban sites: A case-control study

BACKGROUND

Neuroblastoma is the most common extracranial solid tumor in children but its etiology is not clearly understood. While a small fraction of cases might be attributable to genetic factors, the role of environmental pollution factors needs to be assessed.

OBJECTIVES

To ascertain the effect of residential proximity to both industrial and urban areas on neuroblastoma risk, taking into account industrial groups and toxic substances released.

METHODS

We conducted a population-based case-control study of neuroblastoma in Spain, including 398 incident cases gathered from the Spanish Registry of Childhood Tumors (period 1996-2011), and 2388 controls individually matched by year of birth, sex, and region of residence. Distances were computed from the respective subject's residences to the 1271 industries and the 30 urban areas with ≥75,000 inhabitants located in the study area. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (95%CIs) for categories of distance (from 1km to 5km) to industrial and urban pollution sources were calculated, with adjustment for matching variables and socioeconomic confounders.

RESULTS

Excess risk (OR; 95%CI) of neuroblastoma was detected for the intersection between industrial and urban areas: (2.52; 1.20-5.30) for industrial distance of 1km, and (1.99; 1.17-3.37) for industrial distance of 2km. By industrial groups, excess risks were observed near 'Production of metals' (OR=2.05; 95%CI=1.16-3.64 at 1.5km), 'Surface treatment of metals' (OR=1.89; 95%CI=1.10-3.28 at 1km), 'Mines' (OR=5.82; 95%CI=1.04-32.43 at 1.5km), 'Explosives/pyrotechnics' (OR=4.04; 95%CI=1.31-12.42 at 4km), and 'Urban waste-water treatment plants' (OR=2.14; 95%CI=1.08-4.27 at 1.5km).

CONCLUSIONS

These findings support the need for more detailed exposure assessment of certain substances released by these industries.

A Review and Framework for Categorizing Current Research and Development in Health Related Geographical Information Systems (GIS) Studies

OBJECTIVES

The application of GIS in health science has increased over the last decade and new innovative application areas have emerged. This study reviews the literature and builds a framework to provide a conceptual overview of the domain, and to promote strategic planning for further research of GIS in health.

METHOD

The framework is based on literature from the library databases Scopus and Web of Science. The articles were identified based on keywords and initially selected for further study based on titles and abstracts. A grounded theory-inspired method was applied to categorize the selected articles in main focus areas. Subsequent frequency analysis was performed on the identified articles in areas of infectious and non-infectious diseases and continent of origin.

RESULTS

A total of 865 articles were included. Four conceptual domains within GIS in health sciences comprise the framework: spatial analysis of disease, spatial analysis of health service planning, public health, health technologies and tools. Frequency analysis by disease status and location show that malaria and schistosomiasis are the most commonly analyzed infectious diseases where cancer and asthma are the most frequently analyzed non-infectious diseases. Across categories, articles from North America predominate, and in the category of spatial analysis of diseases an equal number of studies concern Asia.

CONCLUSION

Spatial analysis of diseases and health service planning are well-established research areas. The development of future technologies and new application areas for GIS and data-gathering technologies such as GPS, smartphones, remote sensing etc. will be nudging the research in GIS and health.

Effects of deprivation on the geographical variability of larynx cancer incidence in men, Girona (Spain) 1994-2004

OBJECTIVE

To assess the association between the incidence of larynx cancer and socioeconomic conditions in the province of Girona from a spatial viewpoint.

MATERIALS AND METHODS

Incidence cases of larynx cancer (CL) in 1994-2004 were provided by the Girona Cancer Registry. A census tract (CT) was assigned to all patients. Socioeconomic data were extracted from the 2001 Census. A deprivation index for each CT was obtained by principal component analysis, using four socioeconomic indicators. The standardised incidence ratio (SIR) was calculated using the CL incidence rates in the men of the province of Girona assuming a Poisson distribution. Relative risk was obtained applying the Besag, York and Mollié model. The deprivation index was introduced into the model and was categorised in quartiles.

RESULTS

Four hundred and seventy-six incident cases in men were registered. CTs in the lowest deprivation index had a lower risk of larynx cancer, with a risk increase in the higher quartiles. In the highest quartile it was 1.91 times greater than in the lowest. This association was significant when the whole province was considered.

DISCUSSION

The deprivation index explains only part of the geographical variability of CL incidence. Other risk factors without spatial structure may contribute to this explaination.

A test of association between spatially defined exposure patterns and health outcome risk contours

Advances in the availability of geographically referenced health and environmental quality data of high spatial resolution have created new opportunities in environmental epidemiology. Novel statistical methods for linking health, exposure, and hazards are required to underpin the development of public health tracking. A test for the association between spatial contours of health risk and exposure is outlined. This test is examined using, as an example, the spatial contours of congenital malformation risk obtained from a routine dataset in the vicinity of a landfill site and an exposure model based on exponential reduction with distance from the site. Spatial contours of risk of congenital malformation were simulated using the exposure model stated and a given population pattern. These were compared with the corresponding expected risk derived from routine birth data to yield relative risk contours. For each simulation three test statistics were devised: the slope of the regression line of standardized relative risk on exposure level, the proportion of standardized relative risks above zero, and the mean standardized relative risk of individuals not subject to exposure. The distributions of these test statistics (under the null no exposure from site and alternative hypotheses) were determined from a simulation exercise. A comparison of receiver operator characteristic (ROC) curves between those relating to the proposed test and those relating to a widely used method proposed by Stone (1988) demonstrated our test to be more efficient. Formal statistical testing of the concordance between spatial contours of risk and environmental exposure enables optimal use of spatial data.