Risk of prostate cancer in the proximity of industrial installations: A multicase-control study in Spain (MCC-Spain).

BACKGROUND: Prostate cancer (PC) is the second most frequent tumor in men worldwide; however, its etiology remains largely unknown, with the exception of age and family history. The wide variability in incidence/mortality across countries suggests a certain role for environmental exposures that has not yet been clarified. OBJECTIVE: To evaluate the association between risk of PC (by clinical profile) and residential proximity to pollutant industrial installations (by industrial groups, groups of carcinogens, and specific pollutants released), within the context of a Spanish population-based multicase-control study of incident cancer (MCC-Spain). METHODS: This study included 1186 controls and 234 PC cases, frequency matched by age and province of residence. Distances from participants' residences to the 58 industries located in the study area were calculated and categorized into "near" (considering different limits between ≤1 km and ≤ 3 km) or "far" (>3 km). Odds ratios (ORs) and 95 % confidence intervals (95%CIs) were estimated using mixed and multinomial logistic regression models, adjusted for potential confounders and matching variables. RESULTS: No excess risk was detected near the overall industries, with ORs ranging from 0.66 (≤2 km) to 1.11 (≤1 km). However, positive associations (OR; 95%CI) were found, by industrial group, near (≤3 km) industries of ceramic (2.54; 1.28-5.07), food/beverage (2.18; 1.32-3.62), and disposal/recycling of animal waste (2.67; 1.12-6.37); and, by specific pollutant, near plants releasing fluorine (4.65; 1.45-14.91 at ≤1.5 km) and chlorine (5.21; 1.56-17.35 at ≤1 km). In contrast, inverse associations were detected near industries releasing ammonia, methane, dioxins+furans, polycyclic aromatic hydrocarbons, trichloroethylene, and vanadium to air. CONCLUSIONS: The results suggest no association between risk of PC and proximity to the overall industrial installations. However, some both positive and inverse associations were detected near certain industrial groups and industries emitting specific pollutants.

Residential exposure to traffic pollution and mammographic density in premenopausal women.

BACKGROUND: Mammographic density (MD) is the most important breast cancer biomarker. Ambient pollution is a carcinogen, and its relationship with MD is unclear. This study aims to explore the association between exposure to traffic pollution and MD in premenopausal women. METHODOLOGY: This Spanish cross-sectional study involved 769 women attending gynecological examinations in Madrid. Annual Average Daily Traffic (AADT), extracted from 1944 measurement road points provided by the City Council of Madrid, was weighted by distances (d) between road points and women's addresses to develop a Weighted Traffic Exposure Index (WTEI). Three methods were employed: method-1 (1dAADT), method-2 (1dAADT), and method-3 (e1dAADT). Multiple linear regression models, considering both log-transformed percentage of MD and untransformed MD, were used to estimate MD differences by WTEI quartiles, through two strategies: "exposed (exposure buffers between 50 and 200 m) vs. not exposed (>200 m)"; and "degree of traffic exposure". RESULTS: Results showed no association between MD and traffic pollution according to buffers of exposure to the WTEI (first strategy) for the three methods. The highest reductions in MD, although not statistically significant, were detected in the quartile with the highest traffic exposure. For instance, method-3 revealed a suggestive inverse trend (eßQ1 = 1.23, eßQ2 = 0.96, eßQ3 = 0.85, eßQ4 = 0.85, p-trend = 0.099) in the case of 75 m buffer. Similar non-statistically significant trends were observed with Methods-1 and -2. When we examined the effect of traffic exposure considering all the 1944 measurement road points in every participant (second strategy), results showed no association for any of the three methods. A slightly decreased MD, although not significant, was observed only in the quartile with the highest traffic exposure: eßQ4 = 0.98 (method-1), and eßQ4 = 0.95 (methods-2 and -3). CONCLUSIONS: Our results showed no association between exposure to traffic pollution and MD in premenopausal women. Further research is needed to validate these findings.

Mammographic density in the environs of multiple industrial sources.

BACKGROUND: Mammographic density (MD), defined as the percentage of dense fibroglandular tissue in the breast, is a modifiable marker of the risk of developing breast cancer. Our objective was to evaluate the effect of residential proximity to an increasing number of industrial sources in MD. METHODS: A cross-sectional study was conducted on 1225 premenopausal women participating in the DDM-Madrid study. We calculated distances between women's houses and industries. The association between MD and proximity to an increasing number of industrial facilities and industrial clusters was explored using multiple linear regression models. RESULTS: We found a positive linear trend between MD and proximity to an increasing number of industrial sources for all industries, at distances of 1.5 km (p-trend = 0.055) and 2 km (p-trend = 0.083). Moreover, 62 specific industrial clusters were analyzed, highlighting the significant associations found between MD and proximity to the following 6 industrial clusters: cluster 10 and women living at ≤1.5 km (ß = 10.78, 95 % confidence interval (95%CI) = 1.59; 19.97) and at ≤2 km (ß = 7.96, 95%CI = 0.21; 15.70); cluster 18 and women residing at ≤3 km (ß = 8.48, 95%CI = 0.01; 16.96); cluster 19 and women living at ≤3 km (ß = 15.72, 95%CI = 1.96; 29.49); cluster 20 and women living at ≤3 km (ß = 16.95, 95%CI = 2.90; 31.00); cluster 48 and women residing at ≤3 km (ß = 15.86, 95%CI = 3.95; 27.77); and cluster 52 and women living at ≤2.5 km (ß = 11.09, 95%CI = 0.12; 22.05). These clusters include the following industrial activities: surface treatment of metals/plastic, surface treatment using organic solvents, production/processing of metals, recycling of animal waste, hazardous waste, urban waste-water treatment plants, inorganic chemical industry, cement and lime, galvanization, and food/beverage sector. CONCLUSIONS: Our results suggest that women living in the proximity to an increasing number of industrial sources and those near certain types of industrial clusters have higher MD.

Exploring Urban Green Spaces' Effect against Traffic Exposure on Childhood Leukaemia Incidence.

BACKGROUND: Several environmental factors seem to be involved in childhood leukaemia incidence. Traffic exposure could increase the risk while urban green spaces (UGS) exposure could reduce it. However, there is no evidence how these two factors interact on this infant pathology. OBJECTIVES: to evaluate how residential proximity to UGS could be an environmental protective factor against traffic exposure on childhood leukaemia incidence. METHODS: A population-based case control study was conducted across thirty Spanish regions during the period 2000-2018. It included 2526 incident cases and 15,156, individually matched by sex, year-of-birth, and place-of-residence. Using the geographical coordinates of the participants' home residences, a 500 m proxy for exposure to UGS was built. Annual average daily traffic (AADT) was estimated for all types of roads 100 m near the children's residence. Odds ratios (ORs) and 95% confidence intervals (95% CIs), UGS, traffic exposure, and their possible interactions were calculated for overall childhood leukaemia, and the acute lymphoblastic (ALL) and acute myeloblastic leukaemia (AML) subtypes, with adjustment for socio-demographic covariates. RESULTS: We found an increment of childhood leukaemia incidence related to traffic exposure, for every 100 AADT increase the incidence raised 1.1% (95% CI: 0.58-1.61%). UGS exposure showed an incidence reduction for the highest exposure level, Q5 (OR = 0.63; 95% CI = 0.54-0.72). Regression models with both traffic exposure and UGS exposure variables showed similar results but the interaction was not significant. CONCLUSIONS: Despite their opposite effects on childhood leukaemia incidence individually, our results do not suggest a possible interaction between both exposures. This is the first study about the interaction of these two environmental factors; consequently, it is necessary to continue taking into account more individualized data and other possible environmental risk factors involved.

Exploring Blue Spaces' Effects on Childhood Leukaemia Incidence: A Population-Based Case-Control Study in Spain.

BACKGROUND: Blue spaces have been a key part of human evolution, providing resources and helping economies develop. To date, no studies have been carried out to explore how they may be linked to paediatric oncological diseases. OBJECTIVES: To explore the possible relationship of residential proximity to natural and urban blue spaces on childhood leukaemia. METHODS: A population-based case-control study was conducted in four regions of Spain across the period 2000-2018. A total of 936 incident cases and 5616 controls were included, individually matched by sex, year of birth and place of residence. An exposure proxy with four distances (250 m, 500 m, 750 m, and 1 km) to blue spaces was built using the geographical coordinates of the participants' home residences. Odds ratios (ORs) and 95% confidence intervals (95%CIs) for blue-space exposure were calculated for overall childhood leukaemia, and the acute lymphoblastic (ALL) and acute myeloblastic leukaemia (AML) subtypes, with adjustment for socio-demographic and environmental covariates. RESULTS: A decrease in overall childhood leukaemia and ALL-subtype incidence was found as we came nearer to children's places of residence, showing, for the study as a whole, a reduced incidence at 250 m (odds ratio (OR) = 0.77; 95%CI = 0.60-0.97), 500 m (OR = 0.78; 95%CI = 0.65-0.93), 750 m (OR = 0.80; 95%CI = 0.69-0.93), and 1000 m (OR = 0.84; 95%CI = 0.72-0.97). AML model results showed an increasing incidence at closest to subjects' homes (OR at 250m = 1.06; 95%CI=0.63-1.71). CONCLUSIONS: Our results suggest a possible association between lower childhood leukaemia incidence and blue-space proximity. This study is a first approach to blue spaces' possible effects on childhood leukaemia incidence; consequently, it is necessary to continue studying these spaces-while taking into account more individualised data and other possible environmental risk factors.

Residential proximity to industrial pollution and mammographic density.

BACKGROUND: Mammographic density (MD), expressed as percentage of fibroglandular breast tissue, is an important risk factor for breast cancer. Our objective is to investigate the relationship between MD and residential proximity to pollutant industries in premenopausal Spanish women. METHODS: A cross-sectional study was carried out in a sample of 1225 women extracted from the DDM-Madrid study. Multiple linear regression models were used to assess the association of MD percentage (and their 95% confidence intervals (95%CIs)) and proximity (between 1 km and 3 km) to industries included in the European Pollutant Release and Transfer Register. RESULTS: Although no association was found between MD and distance to all industries as a whole, several industrial sectors showed significant association for some distances: "surface treatment of metals and plastic" (ß = 4.98, 95%CI = (0.85; 9.12) at ≤1.5 km, and ß = 3.00, 95%CI = (0.26; 5.73) at ≤2.5 km), "organic chemical industry" (ß = 6.73, 95%CI = (0.50; 12.97) at ≤1.5 km), "pharmaceutical products" (ß = 4.14, 95%CI = (0.58; 7.70) at ≤2 km; ß = 3.55, 95%CI = (0.49; 6.60) at ≤2.5 km; and ß = 3.11, 95%CI = (0.20; 6.01) at ≤3 km), and "urban waste-water treatment plants" (ß = 8.06, 95%CI = (0.82; 15.30) at ≤1 km; ß = 5.28; 95%CI = (0.49; 10.06) at ≤1.5 km; ß = 4.30, 95%CI = (0.03; 8.57) at ≤2 km; ß = 5.26, 95%CI = (1.83; 8.68) at ≤2.5 km; and ß = 3.19, 95%CI = (0.46; 5.92) at ≤3 km). Moreover, significant increased MD was observed in women close to industries releasing specific pollutants: ammonia (ß = 4.55, 95%CI = (0.26; 8.83) at ≤1.5 km; and ß = 3.81, 95%CI = (0.49; 7.14) at ≤2 km), dichloromethane (ß = 3.86, 95%CI = (0.00; 7.71) at ≤2 km), ethylbenzene (ß = 8.96, 95%CI = (0.57; 17.35) at ≤3 km), and phenols (ß = 2.60, 95%CI = (0.21; 5.00) at ≤2.5 km). CONCLUSIONS: Our results suggest no statistically significant relationship between MD and proximity to industries as a whole, although we detected associations with various industrial sectors and some specific pollutants, which suggests that MD could have a mediating role in breast carcinogenesis.