Exposure to Ambient Air Pollution and the Risk of Inflammatory Bowel Disease: A European Nested Case–Control Study

Jorrit L Opstelten; Rob M J Beelen; Max Leenders; Gerard Hoek; Bert Brunekreef; Fiona D M van Schaik; Peter D Siersema; Kirsten T Eriksen; Ole Raaschou-Nielsen; Anne Tjønneland; Kim Overvad; Marie-Christine Boutron-Ruault; Franck Carbonnel; Kees de Hoogh; Timothy J Key; Robert Luben; Simon S M Chan; Andrew R Hart; H Bas Bueno-de-Mesquita; Bas Oldenburg

doi:10.1007/s10620-016-4249-4

. 2016 Jul 26;61(10):2963–2971. doi: 10.1007/s10620-016-4249-4

Exposure to Ambient Air Pollution and the Risk of Inflammatory Bowel Disease: A European Nested Case–Control Study

Jorrit L Opstelten ¹, Rob M J Beelen ^2,³, Max Leenders ², Gerard Hoek ², Bert Brunekreef ², Fiona D M van Schaik ¹, Peter D Siersema ^1,⁴, Kirsten T Eriksen ⁵, Ole Raaschou-Nielsen ^5,⁶, Anne Tjønneland ⁵, Kim Overvad ⁷, Marie-Christine Boutron-Ruault ^8,⁹, Franck Carbonnel ^8,^9,¹⁰, Kees de Hoogh ^11,^12,¹³, Timothy J Key ¹⁴, Robert Luben ¹⁵, Simon S M Chan ^16,¹⁷, Andrew R Hart ^16,¹⁷, H Bas Bueno-de-Mesquita ^1,^18,^19,²⁰, Bas Oldenburg ^1,^✉

¹Department of Gastroenterology and Hepatology, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands

²Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands

³Center for Sustainability, Environment and Health, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands

⁴Department of Gastroenterology and Hepatology, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands

⁵Danish Cancer Society Research Center, Strandboulevarden 49, 2100 Copenhagen Ø, Denmark

⁶Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark

⁷Section for Epidemiology, Department of Public Health, Aarhus University, Bartholins Allé 2, 8000 Aarhus C, Denmark

⁸Paris-Saclay University, Université Paris-Sud, Université de Versailles-Saint-Quentin-en-Yvelines (UVSQ), Centre de Recherche en Épidémiologie et Santé des Populations (CESP), U1018, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Gustave Roussy, 114 rue Edouard Vaillant, 94800 Villejuif, France

⁹Institut Gustave Roussy, 114 Rue Edouard Vaillant, 94805 Villejuif, France

¹⁰Department of Gastroenterology, Bicêtre University Hospital, Assistance Publique des Hôpitaux de Paris, 78 Rue du Général Leclerc, 94275 Le Kremlin Bicêtre, France

¹¹Environmental Exposure and Health Unit, Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland

¹²University of Basel, Petersplatz 1, 4001 Basel, Switzerland

¹³MRC-PHE Center for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, South Kensington Campus, London, SW7 2AZ UK

¹⁴Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF UK

¹⁵Strangeways Research Laboratory, Institute of Public Health, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN UK

¹⁶Department of Medicine, Faculty of Medicine and Health Sciences, Norwich Medical School, University of East Anglia, Norwich, NR4 7TJ UK

¹⁷Department of Gastroenterology, Norfolk and Norwich University Hospital NHS Trust, Colney Lane, Norwich, NR4 7UY UK

¹⁸Department for Determinants of Chronic Diseases, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands

¹⁹Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, South Kensington Campus, London, SW7 2AZ UK

²⁰Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Jalan Universiti, 50603 Kuala Lumpur, Malaysia

^✉

Corresponding author.

PMCID: PMC5020109 PMID: 27461060

Abstract

Background

Industrialization has been linked to the etiology of inflammatory bowel disease (IBD).

Aim

We investigated the association between air pollution exposure and IBD.

Methods

The European Prospective Investigation into Cancer and Nutrition cohort was used to identify cases with Crohn’s disease (CD) (n = 38) and ulcerative colitis (UC) (n = 104) and controls (n = 568) from Denmark, France, the Netherlands, and the UK, matched for center, gender, age, and date of recruitment. Air pollution data were obtained from the European Study of Cohorts for Air Pollution Effects. Residential exposure was assessed with land-use regression models for particulate matter with diameters of <10 μm (PM₁₀), <2.5 μm (PM_2.5), and between 2.5 and 10 μm (PM_coarse), soot (PM_{2.5 absorbance}), nitrogen oxides, and two traffic indicators. Conditional logistic regression analyses were performed to calculate odds ratios (ORs) with 95 % confidence intervals (CIs).

Results

Although air pollution was not significantly associated with CD or UC separately, the associations were mostly similar. Individuals with IBD were less likely to have higher exposure levels of PM_2.5 and PM₁₀, with ORs of 0.24 (95 % CI 0.07–0.81) per 5 μg/m³ and 0.25 (95 % CI 0.08–0.78) per 10 μg/m³, respectively. There was an inverse but nonsignificant association for PM_coarse. A higher nearby traffic load was positively associated with IBD [OR 1.60 (95 % CI 1.04–2.46) per 4,000,000 motor vehicles × m per day]. Other air pollutants were positively but not significantly associated with IBD.

Conclusion

Exposure to air pollution was not found to be consistently associated with IBD.

Electronic supplementary material

The online version of this article (doi:10.1007/s10620-016-4249-4) contains supplementary material, which is available to authorized users.

Keywords: Air pollution, Particulate matter, Inflammatory bowel disease, Crohn’s disease, Ulcerative colitis

Introduction

Inflammatory bowel disease (IBD) is a disabling intestinal condition of unclear etiology affecting over two million people in Europe alone [1]. Both Crohn’s disease (CD) and ulcerative colitis (UC), the two main forms of IBD, are thought to result from a complex interplay between the immune system and gut microbiota in genetically susceptible individuals [2]. Yet, the changing epidemiology of IBD supports a key role for environmental factors in the development of this chronic disorder [3].

The incidence of IBD in Western countries has increased over the last century but currently appears relatively stable, whereas a rapid disease emergence is observed in developing nations, where IBD was formerly uncommon [4, 5]. Consequently, industrialization and westernization of lifestyle have been linked to the etiology of CD and UC [3, 6, 7]. Although various risk factors, such as diet [8], have previously been proposed, these do not fully explain the increase in the incidence of IBD and other environmental changes must therefore be involved [9].

Air pollution is associated with industrialization and consists of a complex mixture of different substances, such as particulate matter (PM). Although air pollution has mainly been associated with cardiorespiratory disorders [10], limited experimental and epidemiological data suggest that air pollutants may also exert deleterious gastrointestinal effects [11]. Potential mechanisms by which air pollutants may cause intestinal injury are thought to include direct adverse effects on epithelial cells, alterations in immune responses, or modulation of the gut microbiota [11–14].

Epidemiological studies examining the relationship between air pollution and IBD are scarce. In a case–control study from the UK, children and young adults, but not older individuals, living in areas with high-level exposure to nitrogen dioxide (NO₂) and sulfur dioxide had an increased risk of developing CD and UC, respectively, indicating possible age-related effects [15]. However, this study was based on regional air pollution estimates, limiting exposure assessment. Therefore, we aimed to investigate the association between residential exposure to ambient air pollution and IBD in a nested case–control study within a multicenter European cohort. Based on previous studies, we hypothesized that air pollution exposure increases the risk of developing CD and UC.

Materials and Methods

Study Population

Subjects were identified from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a large multicenter cohort investigation designed to explore the association between lifestyle and environmental factors and chronic diseases. The methods of the main study were described previously [16]. In the present study, we made use of cases and controls drawn from a subset of this cohort, namely 227,620 initially healthy men and women recruited from five centers in Denmark, France, the Netherlands, and the UK between 1993 and 2000 (Table 1). At baseline, participants provided information on age, gender, habitual diet, and lifestyle factors, including smoking and physical activity, by self-administered questionnaires. Participants’ height and weight were measured by trained health professionals or obtained through self-reports.

Table 1.

Participating centers, study areas, and characteristics of the individual cohorts

Country and center	Individual EPIC cohort	Study area ESCAPE	Cohort size	Nature of cohort	No. of incident CD cases^a	No. of incident UC cases^a
Denmark, Aarhus, and Copenhagen	DCH	Copenhagen area	57,054	Population-based cohort of men and women aged 50–64 years. Enrollment period 1993–1997. Cases identified up to July 2007	11	30
France, regions throughout country	E3N	Paris, Lyon, Grenoble and, Marseille	72,996	Female teachers and co-workers aged 40–65 years from a nationwide health insurance scheme. Enrollment period 1993–1997. Cases identified up to April 2008	5	10
The Netherlands, Bilthoven	MORGEN	Large regions of the country	22,715	Population-based cohort of men and women aged 20–65 years. Enrollment period 1993–1997. Cases identified up to December 2009	9	27
The Netherlands, Utrecht	Prospect	Large regions of the country	17,357	Women aged 49–70 years in a breast cancer screening program. Enrollment period 1993–1997. Cases identified up to December 2009	7	14
The UK, Oxford	Oxford	Large regions of the country	57,498	Members of vegetarian societies and readers of health food magazines aged 20–80 years. Enrollment period 1993–2000. Cases identified up to May 2004	6	23
Total			227,620		38	104

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CD, Crohn’s disease; DCH, Danish Diet, Cancer and Health cohort; E3N, Etude Épidémiologique des femmes de la Mutuelle Générale de l’Education Nationale; EPIC, European Prospective Investigation into Cancer and Nutrition; ESCAPE, European Study of Cohorts for Air Pollution Effects; UC, ulcerative colitis

^aOnly incident cases (and their controls) with air pollution estimates were selected

Exposure Assessment

Air pollution data were obtained from the European Study of Cohorts for Air Pollution Effects (ESCAPE). The ESCAPE project was initiated to investigate the health effects of air pollution within European countries by linking exposure data to health data from ongoing cohort studies, including EPIC [17]. The study areas of ESCAPE generally included major cities with surrounding rural areas and included large regions of the country in some cohorts (Table 1). The methods of the standardized measurement procedures were published elsewhere [18, 19]. In summary, for each study area of ESCAPE, particulate matter with an aerodynamic diameter of <10 μm (PM₁₀), particulate matter with an aerodynamic diameter of <2.5 μm (PM_2.5), blackness of the PM_2.5 exposed filter (PM_{2.5 absorbance}) (a marker for black carbon or soot), nitrogen oxides (NO_x) and NO₂ were measured within 1 year during three different seasons between 2008 and 2011 in at least 20 sites [20, 21]. The concentration of PM_coarse was calculated as the difference between concentrations of PM₁₀ and PM_2.5. Subsequently, the annual average concentration of each pollutant was calculated. Air pollution exposure at the baseline residential address of study participants was then estimated by land-use regression models. These models were developed for each pollutant in each study area to explain the spatial variation of air pollution concentrations, taking various geographical factors into account, including altitude, population density, industrial land use, green space, and traffic flow variables. In addition to the air pollution concentrations, within ESCAPE two traffic indicators at the participant’s residential address were evaluated: traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads in a 100-m buffer (sum of traffic intensity multiplied by the length of those roads). Considering that air pollution was measured after enrollment, concentrations were back-extrapolated to the baseline year of each participant according to a standardized protocol used in previous ESCAPE work [17]. Back-extrapolation was only possible for pollutants for which historical data were available.

Cases and Controls

The cohort was followed up until at least June 2004 and in some centers up to December 2009. Individuals with incident CD or UC were identified using population-based disease registries (Denmark, the Netherlands) or follow-up questionnaires (France, the UK). The medical reports of all potential cases were reviewed by local gastroenterologists to confirm the diagnoses and to obtain information on diagnostic investigations and disease extent. In this nested case–control analysis, each case was matched with four randomly selected unique controls for center, gender, age at recruitment (±6 months), and date of recruitment (±3 months). Controls were alive and had no CD, UC, microscopic or indeterminate colitis on the date of diagnosis of their matched case (incidence density sampling). For the present study, only cases with available air pollution estimates could be included. As the selection of controls was performed prior to the current study and the study areas of ESCAPE did not always cover the entire geographical area of the individual EPIC cohorts, air pollution measures were not available for all controls of a case.

Statistical Analysis

Continuous data were expressed as medians with percentiles, because of the skewed distribution. Categorical data were expressed as frequencies with percentages. Correlations between the individual air pollution measures and traffic indicators were assessed using the Pearson correlation coefficient. Air pollutant concentrations were divided into tertiles according to the distribution across all matched controls. Conditional logistic regression analyses were performed to determine the association between air pollution exposure and IBD. Accordingly, associations were assessed within each cohort rather than between study areas. Considering the relatively small numbers of cases, associations were studied for CD and UC separately and combined. Odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated to estimate the risk of IBD according to the different air pollutant concentrations and traffic indicators used as continuous and categorical variables. In a multivariable model, analyses were adjusted for smoking status (categorized into never smoker, former smoker, and current smoker) and socioeconomic status using educational level (categorized into primary school, technical school, secondary school, and higher education) as previous studies documented associations between these factors and IBD [22, 23]. All models for traffic indicators were additionally adjusted for background NO₂ concentration. Trends across tertiles were computed using the median value of each tertile as a continuous variable. In sensitivity analyses, analyses were repeated for air pollutant concentrations back-extrapolated to the baseline year of participants. Two-sided p values below 0.05 were considered statistically significant. All analyses were performed using SPSS version 21 (IBM Corp., Armonk, NY, USA).

Ethical Considerations

The original cohort studies were approved by the institutional medical ethics committees.

Results

A total of 38 CD cases (median age at diagnosis 56.2 years, 76.3 % female) and 104 UC cases (median age at diagnosis 55.2 years, 70.2 % female) with air pollution measures were identified (Table 2). The median time between recruitment and diagnosis was 4.5 years [interquartile range (IQR) 2.3–6.8 years] and 3.8 years (IQR 2.1–6.4 years) for CD and UC, respectively. Fourteen CD cases (36.9 %) had ileal disease. Left-sided colitis (involvement limited up to the splenic flexure) was the commonest disease phenotype in UC cases (n = 45, 43.6 %). Air pollution estimates were available for 100, 90, 83, 70, and 27 % of controls from the Dutch Prospect cohort, the British cohort, the Dutch MORGEN cohort, the Danish cohort, and the French cohort, respectively. The distribution of air pollutant concentrations and traffic indicators for all IBD cases and controls per individual cohort is presented in Supplementary Tables 1–5. These tables show that within cohorts, pollution distributions were generally very similar between cases and controls and that in some cohorts, the concentration ranges of especially PM_2.5 and PM₁₀ were very small. The correlations between these estimates are presented in Supplementary Tables 6–10.

Table 2.

Characteristics of inflammatory bowel disease cases and controls

	CD cases (n = 38)	Controls (n = 152)	UC cases (n = 104)	Controls (n = 416)
Female, n (%)	29 (76.3)	116 (76.3)	73 (70.2)	292 (70.2)
Age (years) at recruitment, median (IQR)	50.9 (44.7–60.9)	50.3 (44.5–59.0)	50.7 (43.2–56.1)	50.9 (43.2–56.6)
Age (years) at diagnosis, median (IQR)	56.2 (49.7–63.6)	–	55.2 (48.1–60.9)	–
Distribution of Crohn’s disease, n (%)
L1, ileal	14 (36.9)	–	–	–
L2, colonic	13 (34.2)	–	–	–
L3, ileocolonic	10 (26.3)	–	–	–
+ L4, upper gastrointestinal disease	1 (2.6)	–	–	–
Unknown	0 (0.0)	–	–	–
Distribution of ulcerative colitis, n (%)
E1, ulcerative proctitis	–	–	25 (24.3)	–
E2, left-sided colitis	–	–	45 (43.6)	–
E3, extensive colitis	–	–	26 (25.2)	–
Unknown	–	–	7 (6.8)	–
Smoking status at recruitment, n (%)
Never smoker	13 (34.2)	52 (34.2)	36 (34.6)	180 (43.3)
Former smoker	10 (26.3)	54 (35.5)	34 (32.7)	118 (28.4)
Current smoker	15 (39.5)	44 (28.9)	33 (31.7)	116 (27.9)
Unknown	0 (0.0)	2 (1.3)	1 (1.0)	2 (0.5)
Highest educational level at recruitment, n (%)
Primary school	4 (10.5)	29 (19.1)	15 (14.4)	61 (14.7)
Technical school	17 (44.7)	38 (25.0)	36 (34.6)	128 (30.8)
Secondary school	10 (26.3)	39 (25.7)	22 (21.2)	91 (21.9)
Higher education	7 (18.4)	45 (29.6)	27 (26.0)	116 (27.9)
Not specified	0 (0.0)	1 (0.7)	4 (3.8)	14 (3.4)
Unknown	0 (0.0)	0 (0.0)	0 (0.0)	6 (1.4)

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CD Crohn’s disease, IQR interquartile range, UC ulcerative colitis

No statistically significant associations were detected between air pollution exposure and either CD (Table 3) or UC (Table 4), apart from a positive association for total traffic load on all major roads within a 100-m buffer [OR 1.58 (95 % CI 1.00–2.49) per 4,000,000 motor vehicles m per day] in the crude analysis of UC. The effect sizes were largely similar for the univariable and multivariable analyses and for CD and UC. In the crude analysis of CD and UC combined, residential exposure to PM_2.5 was inversely associated with IBD, with an OR of 0.28 (95 % CI 0.08–0.94) per 5 μg/m³ (Table 5). A positive association was found for total traffic load on all major roads [OR 1.60 (95 % CI 1.06–2.43) per 4,000,000 motor vehicles × m per day]. These associations remained statistically significant with similar effect sizes after adjusting for smoking status and educational level in the multivariable analysis. Additionally, PM₁₀ concentrations were inversely associated with IBD in the multivariable model, with an OR of 0.25 (95 % CI 0.08–0.78) per 10 μg/m³. Excluding data of the French cohort, which had the lowest proportion of IBD cases (n = 15) and controls with air pollution measures (n = 20), did not affect the direction of the effect sizes materially (data not shown). The associations for PM_2.5 per cohort are presented in Supplementary Fig. 1. In the analysis based on tertiles, significant inverse associations were detected for PM_2.5 (p _trend = 0.01) and PM_coarse (p _trend = 0.04) in IBD (Supplementary Table 11). Air pollution estimates back-extrapolated to the baseline year of each participant were generally higher than those during 2008–2011. Although no statistically significant associations were found, the sensitivity analyses for IBD for back-extrapolated concentrations of NO₂, NO_x, PM_{2.5 absorbance} and PM₁₀ showed similar effect sizes as for nonback-extrapolated concentrations, apart from PM_{2.5 absorbance} (Table 5).

Table 3.

Association between air pollution exposure and Crohn’s disease (n = 38 cases)

	Odds of CD
	Unadjusted OR (95 % CI)	Adjusted OR (95 % CI)^a
NO₂	1.25 (0.68–2.30)	1.13 (0.59–2.16)
NO_x	1.26 (0.75–2.12)	1.17 (0.67–2.03)
PM_2.5	0.29 (0.03–2.71)	0.12 (0.01–1.77)
PM_{2.5 absorbance}	0.59 (0.11–3.03)	0.34 (0.04–3.05)
PM₁₀	0.45 (0.07–2.90)	0.10 (0.01–1.37)
PM_coarse	1.07 (0.17–6.55)	0.59 (0.07–4.98)
Traffic intensity on the nearest road^b	1.18 (0.82–1.70)	1.16 (0.79–1.71)
Traffic intensity on major roads within 100-m buffer^b	1.92 (0.64–5.82)	1.81 (0.50–6.47)

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ORs are presented for the following increments: 10 μg/m³ for NO₂, 20 μg/m³ for NO_x, 5 μg/m³ for PM_2.5, 10⁻⁵ m⁻¹ for PM_{2.5 absorbance}, 10 μg/m³ for PM₁₀, 5 μg/m³ for PM_coarse, 5000 motor vehicles per day for the traffic intensity on the nearest road, 4,000,000 motor vehicles × m per day for the total traffic load on all major roads within a 100-m buffer

CD Crohn’s disease, NO nitrogen oxide, OR odds ratio, PM particulate matter

^aAdjusted for smoking status and educational level

^bAdditionally adjusted for background NO₂ concentration (continuous variable)

Table 4.

Association between air pollution exposure and ulcerative colitis (n = 104 cases)

	Odds of UC
	Unadjusted OR (95 % CI)	Adjusted OR (95 % CI)^a
NO₂	1.03 (0.73–1.46)	0.99 (0.70–1.41)
NO_x	1.06 (0.79–1.43)	1.03 (0.76–1.38)
PM_2.5	0.27 (0.06–1.17)	0.23 (0.05–1.02)
PM_{2.5 absorbance}	1.19 (0.48–2.96)	1.20 (0.48–2.98)
PM₁₀	0.34 (0.09–1.27)	0.28 (0.07–1.07)
PM_coarse	0.38 (0.11–1.35)	0.31 (0.09–1.10)
Traffic intensity on the nearest road^b	1.08 (0.90–1.29)	1.06 (0.88–1.27)
Traffic intensity on major roads within 100-m buffer^b	1.58 (1.00–2.49)	1.55 (0.97–2.46)

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NO nitrogen oxide, OR odds ratio, PM particulate matter, UC ulcerative colitis

^aAdjusted for smoking status and educational level

^bAdditionally adjusted for background NO₂ concentration (continuous variable)

Table 5.

Association between air pollution exposure and inflammatory bowel disease (n = 142 cases)

	Odds of IBD
	Unadjusted OR (95 % CI)	Adjusted OR (95 % CI)^a
NO₂	1.08 (0.80–1.46)	1.05 (0.77–1.42)
NO_x	1.11 (0.86–1.43)	1.08 (0.83–1.40)
PM_2.5	0.28 (0.08–0.94)	0.24 (0.07–0.81)
PM_{2.5 absorbance}	0.99 (0.45–2.17)	1.03 (0.45–2.34)
PM₁₀	0.37 (0.13–1.09)	0.25 (0.08–0.78)
PM_coarse	0.52 (0.19–1.45)	0.42 (0.14–1.20)
Traffic intensity on the nearest road^b	1.09 (0.93–1.28)	1.07 (0.92–1.26)
Traffic intensity on major roads within 100-m buffer^b	1.60 (1.06–2.43)	1.60 (1.04–2.46)
Back-extrapolated NO₂	1.14 (0.78–1.66)	1.07 (0.73–1.59)
Back-extrapolated NO_x	1.15 (0.86–1.55)	1.10 (0.81–1.49)
Back-extrapolated PM_{2.5 absorbance}	0.46 (0.07–3.10)	0.40 (0.06–2.78)
Back-extrapolated PM₁₀	0.20 (0.02–2.22)	0.17 (0.02–2.01)

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IBD inflammatory bowel disease, NO nitrogen oxide, OR odds ratio, PM particulate matter

^aAdjusted for smoking status and educational level

^bAdditionally adjusted for background NO₂ concentration (continuous variable)

Discussion

In this European multicenter study, no consistent association between residential exposure to ambient air pollution and the risk of IBD was found. The effect sizes were mostly similar for CD and UC separately. Individuals with IBD were less likely to have higher exposure levels of PM_2.5 and PM₁₀, whereas a positive association was observed for total traffic load on all major nearby roads. Other air pollutants were mostly positively but not statistically significantly associated with IBD. Although not reaching statistical significance, the effect sizes were broadly similar when back-extrapolating air pollutant concentrations to the participants’ baseline year.

Numerous studies have confirmed the association of ambient air pollution with a variety of diseases, and several underlying biological mechanisms have been proposed [10, 17, 24, 25]. The link between air pollution and intestinal health is, however, less well established with a few studies showing positive associations with colorectal cancer, appendicitis, and nonspecific abdominal pain [26–30]. In this respect, the adverse effects of smoking [31, 32], which may have some resemblance with air pollution, may help indicate the potential impact of air pollution exposure. It is hypothesized that exposure to air pollutants may contribute to the development of intestinal disorders, including IBD, through diverse biological mechanisms. First, ingestion of air pollutants by inhalation or contaminated foods may have direct toxic effects on epithelial cells, which may induce proinflammatory responses and increase gut permeability [11]. Second, various studies have shown that air pollution exposure may result in systemic inflammatory effects, such as changes in circulating cytokines, including tumor necrosis factor alpha [33]. Notably, air pollution has also been related to immunologically mediated disorders that may share some epidemiological and pathogenic aspects with IBD [34]. For instance, exposure to PM₁₀ has been associated with an increased risk of relapse in multiple sclerosis [35], whereas traffic exposure has been found to be positively associated with incident rheumatoid arthritis [36]. Third, it is thought that air pollution may modulate the microbial composition of the gut [14], as recently exemplified in two studies in which PM exposure in mice led to significant alterations in the microbiota and induced acute and chronic intestinal inflammatory responses [12, 13].

To date, very few epidemiological studies explored the effects of air pollution in IBD. In a nested case–control study from the UK, in the whole population, no significant association between air pollution and incident IBD was found [15]. However, children and young adults living in areas with higher levels (within the upper three quintiles) of NO₂ and sulfur dioxide, respectively, were more likely to develop CD [OR 2.31 (95 % CI 1.25–4.28) for individuals aged ≤23 years] and UC [OR 2.00 (95 % CI 1.08–3.72) for individuals aged ≤25 years]. Land-use regression models for more refined exposure assessments could not be incorporated in this study. An ecological analysis from the US related hospitalizations for IBD to air pollution emissions from an emission inventory, but was unable to estimate air pollution concentrations [37]. In our study, which included mainly middle aged to elderly people, we observed opposing associations. This could indicate that different pollutants have differential effects in specific groups. For example, younger people (with a developing immune system) might be more susceptible to air pollutants as compared to older people. Importantly, children and young adults are also likely to spend more time outdoors and near their home, which may increase and better reflect true personal exposure. Exposure assessment may therefore be more accurate in these individuals. There were no statistically significant associations for CD and UC separately, which presumably resulted from the relatively small numbers of cases. Disease-specific results may exist, as previously observed, for example, in the opposing associations for smoking between CD and UC [22], although the effect sizes were mostly similar for both forms of IBD in our study. We observed inverse associations for some pollutants, which appeared largely consistent across centers and in the analyses using pollution exposure as continuous and categorical variables. It remains unclear whether these associations reflect a true causal relationship or that these pollutants are a proxy for other variables. Interestingly, in the earlier mentioned study, PM₁₀ and NO₂ concentrations were inversely associated with CD in individuals aged 44–57 years with ORs of 0.48 (95 % CI 0.29–0.80) and 0.56 (95 % CI 0.33–0.95), respectively [15], demonstrating that inverse associations have previously been observed in older patients in another population using a different methodological approach. Overall, despite previous data suggesting that air pollutants may negatively impact IBD, no coherent associations have currently been confirmed to draw firm conclusions on the putative adverse effects of air pollution exposure in CD and UC, indicating the need for further research.

This study had several strengths. First, the multicenter design enabled us to explore the association between air pollution and IBD in several European countries. Second, a significant advantage over previous studies was the use of land-use regression models to accurately determine small-scale variations in residential exposure to air pollution and traffic intensity for each participant according to a highly standardized protocol. Third, both cases and controls were drawn from the same baseline population, thereby reducing the risk of selection bias. Fourth, to ensure case ascertainment all diagnoses were confirmed by local physicians and participants with indeterminate or microscopic colitis were excluded. Fifth, the number of cases was similar to what was expected, which reduces the likelihood of follow-up bias [38].

Despite nesting in a well-characterized cohort, the limited sample size was an important drawback and our study may have been underpowered to detect statistical differences. Therefore, we chose to evaluate outcomes for CD and UC separately and for total IBD. Furthermore, air pollution estimates were assessed only at the residential address of each participant and not, for example, at their working address, where individuals may also be exposed. This could have resulted in misclassification of exposure. Moreover, air pollution was measured after diagnosis, which was a general issue in epidemiological studies using ESCAPE exposure data, such as in a previous study linking air pollution to mortality [17]. However, previous studies show that spatial air pollution contrasts remain stable over long periods of time and are well predicted with land-use regression models [39–43]. Using back-extrapolation, we evaluated the association for some pollutants at the baseline year of each participant, with effect sizes being broadly similar to the main analyses. It has been estimated that most of the participants did not move after enrollment [17], but exact data on moving were unavailable for all centers. The majority of cases developed IBD over the age of 50 years, indicating late-onset IBD, whereas CD and UC commonly present at an earlier age. This limited the opportunity to study age-specific effects, and the results may therefore not be generalizable to the whole IBD population as other phenotypes may have different environmental influences. Considering the limited sample size and multiple comparisons, we cannot entirely exclude that our results are due to chance findings. Finally, although we were able to either match or adjust for potential confounders, such as center and smoking, residual confounding (by unknown risk factors) could not be fully excluded in this observational study.

To conclude, we were unable to demonstrate a consistent association between residential exposure to ambient air pollution and IBD risk in this European multicenter cohort.

Electronic supplementary material

Below is the link to the electronic supplementary material.

10620_2016_4249_MOESM1_ESM.tif^{(210.1KB, tif)}

Supplementary Figure 1. Association between PM2.5 exposure and inflammatory bowel disease per cohort. CI: confidence interval; PM2.5: particulate matter with an aerodynamic diameter of less than 2.5 μm; OR: odds ratio. Adjustment for smoking status and educational level. ORs are presented for the following increment: 5 μg/m3 (TIFF 210 kb)

Supplementary material 2 (DOCX 97 kb)^{(97KB, docx)}

Acknowledgments

J.L.O. was supported by an unrestricted research grant from Dr. Falk Pharma. The coordination of the European Prospective Investigation into Cancer and Nutrition (EPIC) study was financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer (IARC). The national cohorts were supported by the Danish Cancer Society (Denmark); Ligue contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, French Institute of Health and Medical Research (INSERM) (France); Dutch Ministry of Health, Welfare and Sports, Dutch Prevention Funds, LK Research Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (the Netherlands); Cancer Research UK C8221/A19170, Medical Research Council MR/M012190/1 (UK). The European Study of Cohorts for Air Pollution Effects (ESCAPE) study has received funding from the European Community’s Seventh Framework Program (FP7/2007-2011) under Grant Agreement No. 211250.

Authors’ contributions

J.L.O., R.M.J.B., H.B.B.-d-M., and B.O were involved in conception and design. J.L.O., R.M.J.B., G.H., B.B., F.D.M.vS., P.D.S., K.T.E., O.R.-N., A.T., K.O., M.-C.B.-R., F.C., K.dH., T.J.K., R.L., S.S.M.C., A.R.H., H.B.B.-d-M., and B.O were involved in acquisition of the data. J.L.O., R.M.J.B., M.L., G.H., B.B., B.O were involved in analysis and interpretation of the data. J.L.O was involved in drafting of the manuscript. All authors were involved in critical revision of the manuscript for important intellectual content and gave final approval of the submitted manuscript.

Abbreviations

CD: Crohn’s disease
CI: Confidence interval
EPIC: European Prospective Investigation into Cancer and Nutrition
ESCAPE: European Study of Cohorts for Air Pollution Effects
IBD: Inflammatory bowel disease
NO: Nitrogen oxide
OR: Odds ratio
PM: Particulate matter
UC: Ulcerative colitis

Compliance with ethical standards

Conflict of interest

The authors have no conflicts of interest to disclose.

Footnotes

H Bas Bueno-de-Mesquita and Bas Oldenburg are joint last authors.

Electronic supplementary material

The online version of this article (doi:10.1007/s10620-016-4249-4) contains supplementary material, which is available to authorized users.

References

1.Burisch J, Jess T, Martinato M, Lakatos PL. The burden of inflammatory bowel disease in Europe. J Crohns Colitis. 2013;7:322–337. doi: 10.1016/j.crohns.2013.01.010. [DOI] [PubMed] [Google Scholar]
2.Scharl M, Rogler G. Inflammatory bowel disease pathogenesis: what is new? Curr Opin Gastroenterol. 2012;28:301–309. doi: 10.1097/MOG.0b013e328353e61e. [DOI] [PubMed] [Google Scholar]
3.Ng SC, Bernstein CN, Vatn MH, et al. Geographical variability and environmental risk factors in inflammatory bowel disease. Gut. 2013;62:630–649. doi: 10.1136/gutjnl-2012-303661. [DOI] [PubMed] [Google Scholar]
4.Thia KT, Loftus EV, Jr, Sandborn WJ, Yang SK. An update on the epidemiology of inflammatory bowel disease in Asia. Am J Gastroenterol. 2008;103:3167–3182. doi: 10.1111/j.1572-0241.2008.02158.x. [DOI] [PubMed] [Google Scholar]
5.Molodecky NA, Soon IS, Rabi DM, et al. Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology. 2012;142:46–54. doi: 10.1053/j.gastro.2011.10.001. [DOI] [PubMed] [Google Scholar]
6.Bernstein CN, Shanahan F. Disorders of a modern lifestyle: reconciling the epidemiology of inflammatory bowel diseases. Gut. 2008;57:1185–1191. doi: 10.1136/gut.2007.122143. [DOI] [PubMed] [Google Scholar]
7.Soon IS, Molodecky NA, Rabi DM, Ghali WA, Barkema HW, Kaplan GG. The relationship between urban environment and the inflammatory bowel diseases: a systematic review and meta-analysis. BMC Gastroenterol. 2012;12:51. doi: 10.1186/1471-230X-12-51. [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Hou JK, Abraham B, El-Serag H. Dietary intake and risk of developing inflammatory bowel disease: a systematic review of the literature. Am J Gastroenterol. 2011;106:563–573. doi: 10.1038/ajg.2011.44. [DOI] [PubMed] [Google Scholar]
9.Ananthakrishnan AN. Environmental risk factors for inflammatory bowel diseases: a review. Dig Dis Sci. 2015;60:290–298. doi: 10.1007/s10620-014-3350-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Brunekreef B, Holgate ST. Air pollution and health. Lancet. 2002;360:1233–1242. doi: 10.1016/S0140-6736(02)11274-8. [DOI] [PubMed] [Google Scholar]
11.Beamish LA, Osornio-Vargas AR, Wine E. Air pollution: an environmental factor contributing to intestinal disease. J Crohns Colitis. 2011;5:279–286. doi: 10.1016/j.crohns.2011.02.017. [DOI] [PubMed] [Google Scholar]
12.Kish L, Hotte N, Kaplan GG, et al. Environmental particulate matter induces murine intestinal inflammatory responses and alters the gut microbiome. PLoS One. 2013;8:e62220. doi: 10.1371/journal.pone.0062220. [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Salim SY, Jovel J, Wine E, et al. Exposure to ingested airborne pollutant particulate matter increases mucosal exposure to bacteria and induces early onset of inflammation in neonatal IL-10-deficient mice. Inflamm Bowel Dis. 2014;20:1129–1138. doi: 10.1097/MIB.0000000000000066. [DOI] [PubMed] [Google Scholar]
14.Salim SY, Kaplan GG, Madsen KL. Air pollution effects on the gut microbiota: a link between exposure and inflammatory disease. Gut Microbes. 2014;5:215–219. doi: 10.4161/gmic.27251. [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Kaplan GG, Hubbard J, Korzenik J, et al. The inflammatory bowel diseases and ambient air pollution: a novel association. Am J Gastroenterol. 2010;105:2412–2419. doi: 10.1038/ajg.2010.252. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Riboli E, Hunt KJ, Slimani N, et al. European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002;5:1113–1124. doi: 10.1079/PHN2002394. [DOI] [PubMed] [Google Scholar]
17.Beelen R, Raaschou-Nielsen O, Stafoggia M, et al. Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project. Lancet. 2014;383:785–795. doi: 10.1016/S0140-6736(13)62158-3. [DOI] [PubMed] [Google Scholar]
18.Eeftens M, Beelen R, de Hoogh K, et al. Development of land use regression models for PM2.5, PM2.5 absorbance, PM10 and PMcoarse in 20 European study areas; results of the ESCAPE project. Environ Sci Technol. 2012;46:11195–11205. doi: 10.1021/es301948k. [DOI] [PubMed] [Google Scholar]
19.Beelen R, Hoek G, Vienneau D, et al. Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe—the ESCAPE project. Atmos Environ. 2013;72:10–23. doi: 10.1016/j.atmosenv.2013.02.037. [DOI] [Google Scholar]
20.Cyrys J, Eeftens M, Heinrich J, et al. Variation of NO2 and NOx concentrations between and within 36 European study areas: results from the ESCAPE study. Atmos Environ. 2012;62:374–390. doi: 10.1016/j.atmosenv.2012.07.080. [DOI] [Google Scholar]
21.Eeftens M, Tsai M-Y, Ampe C, et al. Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2—results of the ESCAPE project. Atmos Environ. 2012;62:303–317. doi: 10.1016/j.atmosenv.2012.08.038. [DOI] [Google Scholar]
22.Mahid SS, Minor KS, Soto RE, Hornung CA, Galandiuk S. Smoking and inflammatory bowel disease: a meta-analysis. Mayo Clin Proc. 2006;81:1462–1471. doi: 10.4065/81.11.1462. [DOI] [PubMed] [Google Scholar]
23.Aamodt G, Jahnsen J, Bengtson MB, Moum B, Vatn MH. Geographic distribution and ecological studies of inflammatory bowel disease in southeastern Norway in 1990–1993. Inflamm Bowel Dis. 2008;14:984–991. doi: 10.1002/ibd.20417. [DOI] [PubMed] [Google Scholar]
24.Mills NL, Donaldson K, Hadoke PW, et al. Adverse cardiovascular effects of air pollution. Nat Clin Pract Cardiovasc Med. 2009;6:36–44. doi: 10.1038/ncpcardio1399. [DOI] [PubMed] [Google Scholar]
25.Langrish JP, Bosson J, Unosson J, et al. Cardiovascular effects of particulate air pollution exposure: time course and underlying mechanisms. J Intern Med. 2012;272:224–239. doi: 10.1111/j.1365-2796.2012.02566.x. [DOI] [PubMed] [Google Scholar]
26.Calvert GM, Ward E, Schnorr TM, Fine LJ. Cancer risks among workers exposed to metalworking fluids: a systematic review. Am J Ind Med. 1998;33:282–292. doi: 10.1002/(SICI)1097-0274(199803)33:3<282::AID-AJIM10>3.0.CO;2-W. [DOI] [PubMed] [Google Scholar]
27.García-Pérez J, López-Cima MF, Pérez-Gómez B, et al. Mortality due to tumours of the digestive system in towns lying in the vicinity of metal production and processing installations. Sci Total Environ. 2010;408:3102–3112. doi: 10.1016/j.scitotenv.2010.03.051. [DOI] [PubMed] [Google Scholar]
28.Kaplan GG, Dixon E, Panaccione R, et al. Effect of ambient air pollution on the incidence of appendicitis. CMAJ. 2009;181:591–597. doi: 10.1503/cmaj.082068. [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Orazzo F, Nespoli L, Ito K, et al. Air pollution, aeroallergens, and emergency room visits for acute respiratory diseases and gastroenteric disorders among young children in six Italian cities. Environ Health Perspect. 2009;117:1780–1785. doi: 10.1289/ehp.0900599. [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Kaplan GG, Szyszkowicz M, Fichna J, et al. Non-specific abdominal pain and air pollution: a novel association. PLoS One. 2012;7:e47669. doi: 10.1371/journal.pone.0047669. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Silverstein MD, Lashner BA, Hanauer SB, Evans AA, Kirsner JB. Cigarette smoking in Crohn’s disease. Am J Gastroenterol. 1989;84:31–33. [PubMed] [Google Scholar]
32.Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve P. Smoking and colorectal cancer: a meta-analysis. JAMA. 2008;300:2765–2778. doi: 10.1001/jama.2008.839. [DOI] [PubMed] [Google Scholar]
33.van Eeden SF, Tan WC, Suwa T, et al. Cytokines involved in the systemic inflammatory response induced by exposure to particulate matter air pollutants (PM(10)) Am J Respir Crit Care Med. 2001;164:826–830. doi: 10.1164/ajrccm.164.5.2010160. [DOI] [PubMed] [Google Scholar]
34.Cohen R, Robinson D, Jr, Paramore C, Fraeman K, Renahan K, Bala M. Autoimmune disease concomitance among inflammatory bowel disease patients in the United States, 2001–2002. Inflamm Bowel Dis. 2008;14:738–743. doi: 10.1002/ibd.20406. [DOI] [PubMed] [Google Scholar]
35.Oikonen M, Laaksonen M, Laippala P, et al. Ambient air quality and occurrence of multiple sclerosis relapse. Neuroepidemiology. 2003;22:95–99. doi: 10.1159/000067108. [DOI] [PubMed] [Google Scholar]
36.Hart JE, Laden F, Puett RC, Costenbader KH, Karlson EW. Exposure to traffic pollution and increased risk of rheumatoid arthritis. Environ Health Perspect. 2009;117:1065–1069. doi: 10.1289/ehp.0800503. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Ananthakrishnan AN, McGinley EL, Binion DG, Saeian K. Ambient air pollution correlates with hospitalizations for inflammatory bowel disease: an ecologic analysis. Inflamm Bowel Dis. 2011;17:1138–1145. doi: 10.1002/ibd.21455. [DOI] [PubMed] [Google Scholar]
38.Shivananda S, Lennard-Jones J, Logan R, et al. Incidence of inflammatory bowel disease across Europe: is there a difference between north and south? Results of the European Collaborative Study on Inflammatory Bowel Disease (EC-IBD) Gut. 1996;39:690–697. doi: 10.1136/gut.39.5.690. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Beelen R, Hoek G, Fischer P, van den Brandt PA, Brunekreef B. Estimated long-term outdoor air pollution concentrations in a cohort study. Atmos Environ. 2007;41:1343–1358. doi: 10.1016/j.atmosenv.2006.10.020. [DOI] [Google Scholar]
40.Eeftens M, Beelen R, Fischer P, Brunekreef B, Meliefste K, Hoek G. Stability of measured and modelled spatial contrasts in NO2 over time. Occup Environ Med. 2011;68:765–770. doi: 10.1136/oem.2010.061135. [DOI] [PubMed] [Google Scholar]
41.Cesaroni G, Porta D, Badaloni C, et al. Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study. Environ Health. 2012;11:48. doi: 10.1186/1476-069X-11-48. [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Wang R, Henderson SB, Sbihi H, Allen RW, Brauer M. Temporal stability of land use regression models for traffic-related air pollution. Atmos Environ. 2013;64:312–319. doi: 10.1016/j.atmosenv.2012.09.056. [DOI] [Google Scholar]
43.Gulliver J, de Hoogh K, Hansell A, Vienneau D. Development and back-extrapolation of NO2 land use regression models for historic exposure assessment in Great Britain. Environ Sci Technol. 2013;47:7804–7811. doi: 10.1021/es4008849. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

10620_2016_4249_MOESM1_ESM.tif^{(210.1KB, tif)}

Supplementary material 2 (DOCX 97 kb)^{(97KB, docx)}

[CR1] 1.Burisch J, Jess T, Martinato M, Lakatos PL. The burden of inflammatory bowel disease in Europe. J Crohns Colitis. 2013;7:322–337. doi: 10.1016/j.crohns.2013.01.010. [DOI] [PubMed] [Google Scholar]

[CR2] 2.Scharl M, Rogler G. Inflammatory bowel disease pathogenesis: what is new? Curr Opin Gastroenterol. 2012;28:301–309. doi: 10.1097/MOG.0b013e328353e61e. [DOI] [PubMed] [Google Scholar]

[CR3] 3.Ng SC, Bernstein CN, Vatn MH, et al. Geographical variability and environmental risk factors in inflammatory bowel disease. Gut. 2013;62:630–649. doi: 10.1136/gutjnl-2012-303661. [DOI] [PubMed] [Google Scholar]

[CR4] 4.Thia KT, Loftus EV, Jr, Sandborn WJ, Yang SK. An update on the epidemiology of inflammatory bowel disease in Asia. Am J Gastroenterol. 2008;103:3167–3182. doi: 10.1111/j.1572-0241.2008.02158.x. [DOI] [PubMed] [Google Scholar]

[CR5] 5.Molodecky NA, Soon IS, Rabi DM, et al. Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology. 2012;142:46–54. doi: 10.1053/j.gastro.2011.10.001. [DOI] [PubMed] [Google Scholar]

[CR6] 6.Bernstein CN, Shanahan F. Disorders of a modern lifestyle: reconciling the epidemiology of inflammatory bowel diseases. Gut. 2008;57:1185–1191. doi: 10.1136/gut.2007.122143. [DOI] [PubMed] [Google Scholar]

[CR7] 7.Soon IS, Molodecky NA, Rabi DM, Ghali WA, Barkema HW, Kaplan GG. The relationship between urban environment and the inflammatory bowel diseases: a systematic review and meta-analysis. BMC Gastroenterol. 2012;12:51. doi: 10.1186/1471-230X-12-51. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Hou JK, Abraham B, El-Serag H. Dietary intake and risk of developing inflammatory bowel disease: a systematic review of the literature. Am J Gastroenterol. 2011;106:563–573. doi: 10.1038/ajg.2011.44. [DOI] [PubMed] [Google Scholar]

[CR9] 9.Ananthakrishnan AN. Environmental risk factors for inflammatory bowel diseases: a review. Dig Dis Sci. 2015;60:290–298. doi: 10.1007/s10620-014-3350-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Brunekreef B, Holgate ST. Air pollution and health. Lancet. 2002;360:1233–1242. doi: 10.1016/S0140-6736(02)11274-8. [DOI] [PubMed] [Google Scholar]

[CR11] 11.Beamish LA, Osornio-Vargas AR, Wine E. Air pollution: an environmental factor contributing to intestinal disease. J Crohns Colitis. 2011;5:279–286. doi: 10.1016/j.crohns.2011.02.017. [DOI] [PubMed] [Google Scholar]

[CR12] 12.Kish L, Hotte N, Kaplan GG, et al. Environmental particulate matter induces murine intestinal inflammatory responses and alters the gut microbiome. PLoS One. 2013;8:e62220. doi: 10.1371/journal.pone.0062220. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Salim SY, Jovel J, Wine E, et al. Exposure to ingested airborne pollutant particulate matter increases mucosal exposure to bacteria and induces early onset of inflammation in neonatal IL-10-deficient mice. Inflamm Bowel Dis. 2014;20:1129–1138. doi: 10.1097/MIB.0000000000000066. [DOI] [PubMed] [Google Scholar]

[CR14] 14.Salim SY, Kaplan GG, Madsen KL. Air pollution effects on the gut microbiota: a link between exposure and inflammatory disease. Gut Microbes. 2014;5:215–219. doi: 10.4161/gmic.27251. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Kaplan GG, Hubbard J, Korzenik J, et al. The inflammatory bowel diseases and ambient air pollution: a novel association. Am J Gastroenterol. 2010;105:2412–2419. doi: 10.1038/ajg.2010.252. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Riboli E, Hunt KJ, Slimani N, et al. European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002;5:1113–1124. doi: 10.1079/PHN2002394. [DOI] [PubMed] [Google Scholar]

[CR17] 17.Beelen R, Raaschou-Nielsen O, Stafoggia M, et al. Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project. Lancet. 2014;383:785–795. doi: 10.1016/S0140-6736(13)62158-3. [DOI] [PubMed] [Google Scholar]

[CR18] 18.Eeftens M, Beelen R, de Hoogh K, et al. Development of land use regression models for PM2.5, PM2.5 absorbance, PM10 and PMcoarse in 20 European study areas; results of the ESCAPE project. Environ Sci Technol. 2012;46:11195–11205. doi: 10.1021/es301948k. [DOI] [PubMed] [Google Scholar]

[CR19] 19.Beelen R, Hoek G, Vienneau D, et al. Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe—the ESCAPE project. Atmos Environ. 2013;72:10–23. doi: 10.1016/j.atmosenv.2013.02.037. [DOI] [Google Scholar]

[CR20] 20.Cyrys J, Eeftens M, Heinrich J, et al. Variation of NO2 and NOx concentrations between and within 36 European study areas: results from the ESCAPE study. Atmos Environ. 2012;62:374–390. doi: 10.1016/j.atmosenv.2012.07.080. [DOI] [Google Scholar]

[CR21] 21.Eeftens M, Tsai M-Y, Ampe C, et al. Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2—results of the ESCAPE project. Atmos Environ. 2012;62:303–317. doi: 10.1016/j.atmosenv.2012.08.038. [DOI] [Google Scholar]

[CR22] 22.Mahid SS, Minor KS, Soto RE, Hornung CA, Galandiuk S. Smoking and inflammatory bowel disease: a meta-analysis. Mayo Clin Proc. 2006;81:1462–1471. doi: 10.4065/81.11.1462. [DOI] [PubMed] [Google Scholar]

[CR23] 23.Aamodt G, Jahnsen J, Bengtson MB, Moum B, Vatn MH. Geographic distribution and ecological studies of inflammatory bowel disease in southeastern Norway in 1990–1993. Inflamm Bowel Dis. 2008;14:984–991. doi: 10.1002/ibd.20417. [DOI] [PubMed] [Google Scholar]

[CR24] 24.Mills NL, Donaldson K, Hadoke PW, et al. Adverse cardiovascular effects of air pollution. Nat Clin Pract Cardiovasc Med. 2009;6:36–44. doi: 10.1038/ncpcardio1399. [DOI] [PubMed] [Google Scholar]

[CR25] 25.Langrish JP, Bosson J, Unosson J, et al. Cardiovascular effects of particulate air pollution exposure: time course and underlying mechanisms. J Intern Med. 2012;272:224–239. doi: 10.1111/j.1365-2796.2012.02566.x. [DOI] [PubMed] [Google Scholar]

[CR26] 26.Calvert GM, Ward E, Schnorr TM, Fine LJ. Cancer risks among workers exposed to metalworking fluids: a systematic review. Am J Ind Med. 1998;33:282–292. doi: 10.1002/(SICI)1097-0274(199803)33:3<282::AID-AJIM10>3.0.CO;2-W. [DOI] [PubMed] [Google Scholar]

[CR27] 27.García-Pérez J, López-Cima MF, Pérez-Gómez B, et al. Mortality due to tumours of the digestive system in towns lying in the vicinity of metal production and processing installations. Sci Total Environ. 2010;408:3102–3112. doi: 10.1016/j.scitotenv.2010.03.051. [DOI] [PubMed] [Google Scholar]

[CR28] 28.Kaplan GG, Dixon E, Panaccione R, et al. Effect of ambient air pollution on the incidence of appendicitis. CMAJ. 2009;181:591–597. doi: 10.1503/cmaj.082068. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR29] 29.Orazzo F, Nespoli L, Ito K, et al. Air pollution, aeroallergens, and emergency room visits for acute respiratory diseases and gastroenteric disorders among young children in six Italian cities. Environ Health Perspect. 2009;117:1780–1785. doi: 10.1289/ehp.0900599. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Kaplan GG, Szyszkowicz M, Fichna J, et al. Non-specific abdominal pain and air pollution: a novel association. PLoS One. 2012;7:e47669. doi: 10.1371/journal.pone.0047669. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Silverstein MD, Lashner BA, Hanauer SB, Evans AA, Kirsner JB. Cigarette smoking in Crohn’s disease. Am J Gastroenterol. 1989;84:31–33. [PubMed] [Google Scholar]

[CR32] 32.Botteri E, Iodice S, Bagnardi V, Raimondi S, Lowenfels AB, Maisonneuve P. Smoking and colorectal cancer: a meta-analysis. JAMA. 2008;300:2765–2778. doi: 10.1001/jama.2008.839. [DOI] [PubMed] [Google Scholar]

[CR33] 33.van Eeden SF, Tan WC, Suwa T, et al. Cytokines involved in the systemic inflammatory response induced by exposure to particulate matter air pollutants (PM(10)) Am J Respir Crit Care Med. 2001;164:826–830. doi: 10.1164/ajrccm.164.5.2010160. [DOI] [PubMed] [Google Scholar]

[CR34] 34.Cohen R, Robinson D, Jr, Paramore C, Fraeman K, Renahan K, Bala M. Autoimmune disease concomitance among inflammatory bowel disease patients in the United States, 2001–2002. Inflamm Bowel Dis. 2008;14:738–743. doi: 10.1002/ibd.20406. [DOI] [PubMed] [Google Scholar]

[CR35] 35.Oikonen M, Laaksonen M, Laippala P, et al. Ambient air quality and occurrence of multiple sclerosis relapse. Neuroepidemiology. 2003;22:95–99. doi: 10.1159/000067108. [DOI] [PubMed] [Google Scholar]

[CR36] 36.Hart JE, Laden F, Puett RC, Costenbader KH, Karlson EW. Exposure to traffic pollution and increased risk of rheumatoid arthritis. Environ Health Perspect. 2009;117:1065–1069. doi: 10.1289/ehp.0800503. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR37] 37.Ananthakrishnan AN, McGinley EL, Binion DG, Saeian K. Ambient air pollution correlates with hospitalizations for inflammatory bowel disease: an ecologic analysis. Inflamm Bowel Dis. 2011;17:1138–1145. doi: 10.1002/ibd.21455. [DOI] [PubMed] [Google Scholar]

[CR38] 38.Shivananda S, Lennard-Jones J, Logan R, et al. Incidence of inflammatory bowel disease across Europe: is there a difference between north and south? Results of the European Collaborative Study on Inflammatory Bowel Disease (EC-IBD) Gut. 1996;39:690–697. doi: 10.1136/gut.39.5.690. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR39] 39.Beelen R, Hoek G, Fischer P, van den Brandt PA, Brunekreef B. Estimated long-term outdoor air pollution concentrations in a cohort study. Atmos Environ. 2007;41:1343–1358. doi: 10.1016/j.atmosenv.2006.10.020. [DOI] [Google Scholar]

[CR40] 40.Eeftens M, Beelen R, Fischer P, Brunekreef B, Meliefste K, Hoek G. Stability of measured and modelled spatial contrasts in NO2 over time. Occup Environ Med. 2011;68:765–770. doi: 10.1136/oem.2010.061135. [DOI] [PubMed] [Google Scholar]

[CR41] 41.Cesaroni G, Porta D, Badaloni C, et al. Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study. Environ Health. 2012;11:48. doi: 10.1186/1476-069X-11-48. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Wang R, Henderson SB, Sbihi H, Allen RW, Brauer M. Temporal stability of land use regression models for traffic-related air pollution. Atmos Environ. 2013;64:312–319. doi: 10.1016/j.atmosenv.2012.09.056. [DOI] [Google Scholar]

[CR43] 43.Gulliver J, de Hoogh K, Hansell A, Vienneau D. Development and back-extrapolation of NO2 land use regression models for historic exposure assessment in Great Britain. Environ Sci Technol. 2013;47:7804–7811. doi: 10.1021/es4008849. [DOI] [PubMed] [Google Scholar]

PERMALINK

Exposure to Ambient Air Pollution and the Risk of Inflammatory Bowel Disease: A European Nested Case–Control Study

Jorrit L Opstelten

Rob M J Beelen

Max Leenders

Gerard Hoek

Bert Brunekreef

Fiona D M van Schaik

Peter D Siersema

Kirsten T Eriksen

Ole Raaschou-Nielsen

Anne Tjønneland

Kim Overvad

Marie-Christine Boutron-Ruault

Franck Carbonnel

Kees de Hoogh

Timothy J Key

Robert Luben

Simon S M Chan

Andrew R Hart

H Bas Bueno-de-Mesquita

Bas Oldenburg

Abstract

Background

Aim

Methods

Results

Conclusion

Electronic supplementary material

Introduction

Materials and Methods

Study Population

Table 1.

Exposure Assessment

Cases and Controls

Statistical Analysis

Ethical Considerations

Results

Table 2.

Table 3.

Table 4.

Table 5.

Discussion

Electronic supplementary material

Acknowledgments

Authors’ contributions

Abbreviations

Compliance with ethical standards

Conflict of interest

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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