Skip to main content
Erschienen in: European Journal of Epidemiology 9/2016

Open Access 21.03.2016 | REVIEW

Modifiable risk factors for the prevention of bladder cancer: a systematic review of meta-analyses

verfasst von: Abdulmohsen H. Al-Zalabani, Kelly F. J. Stewart, Anke Wesselius, Annemie M. W. J. Schols, Maurice P. Zeegers

Erschienen in: European Journal of Epidemiology | Ausgabe 9/2016

Abstract

Each year, 430,000 people are diagnosed with bladder cancer. Due to the high recurrence rate of the disease, primary prevention is paramount. Therefore, we reviewed all meta-analyses on modifiable risk factors of primary bladder cancer. PubMed, Embase and Cochrane database were systematically searched for meta-analyses on modifiable risk factors published between 1995 and 2015. When appropriate, meta-analyses (MA) were combined in meta–meta-analysis (MMA). If not, the most comprehensive MA was selected based on the number of primary studies included. Probability of causation was calculated for individual factors and a subset of lifestyle factors combined. Of 1496 articles identified, 5 were combined in MMA and 21 were most comprehensive on a single risk factor. Statistically significant associations were found for current (RR 3.14) or former (RR 1.83) cigarette smoking, pipe (RR 1.9) or cigar (RR 2.3) smoking, antioxidant supplementation (RR 1.52), obesity (RR 1.10), higher physical activity levels (RR 0.86), higher body levels of selenium (RR 0.61) and vitamin D (RR 0.75), and higher intakes of: processed meat (RR 1.22), vitamin A (RR 0.82), vitamin E (RR 0.82), folate (RR 0.84), fruit (RR 0.77), vegetables (RR 0.83), citrus fruit (RR 0.85), and cruciferous vegetables (RR 0.84). Finally, three occupations with the highest risk were tobacco workers (RR 1.72), dye workers (RR 1.58), and chimney sweeps (RR 1.53). The probability of causation for individual factors ranged from 4 to 68 %. The combined probability of causation was 81.8 %. Modification of lifestyle and occupational exposures can considerably reduce the bladder cancer burden. While smoking remains one of the key risk factors, also several diet-related and occupational factors are very relevant.
Hinweise
Review registration: PROSPERO CRD42015023411.
Abdulmohsen H. Al-Zalabani, and Kelly F. J. Stewart have contributed equally to this work.

Introduction

The International Agency for Research on Cancer (IARC) estimated that worldwide 430,000 people were diagnosed with bladder cancer in 2012, with an age-standardised rate (ASR) of 5.3 per 100,000 people. Incidence of bladder cancer is particularly high in males with 77 % of the cases, ranking it the 7th highest on incidence and 9th highest on mortality. For females it is the 19th highest on incidence and 17th highest on mortality. The incidence of bladder cancer is almost 3 times higher in more developed countries compared to less developed countries (ASR of 9.5 and 3.3 per 100,000 respectively) [1].
Several genetic polymorphisms have been proposed to be associated with the development of bladder cancer. However, genetic effects can explain ‘only’ 7 % of the bladder cancer incidence in western populations [2], and therefore, risk factors related to lifestyle, environmental, and occupational exposures could potentially play an important role in the development of this disease. Over the years, multiple external risk factors have been proposed. Well-established risk factors are tobacco consumption, occupational exposure, such as to aromatic amines and Polycyclic Aromatic Hydrocarbons (PAHs), and infection with Schistosoma hematobium [3]. Whereas smoking is the most important risk factor in developed countries, S. hematobium infection accounts for the largest burden in African countries [4, 5]. Additional suggested risk factors are, amongst others, alcohol consumption, coffee intake, low fruit, and vegetable consumption, low selenium and vitamin E intake, pollution of drinking water, and several medical treatments [3, 6].
Exposure to some of the key risk factors of bladder cancer has been successfully reduced in the population. For example, the reduction in exposure to aromatic amines seemed to be directly related to a reduction in bladder cancer incidence [7]. Men are generally more exposed to occupational risk factors of bladder cancer and it is estimated that 7.1 % of the bladder cancer cases in men can be attributed to occupational factors [8]. Also, the prevalence rates of smoking have been declining significantly over the past decades, although the absolute number of smokers has been increasing due to the growing world population [9]. Because men smoke more than women, the percentage of cases attributable to smoking is higher in males than in females: 42.8 % (males) versus 25.7 % (females) in Europe, and 34.3 % (males) versus 30.1 % (females) in the United States [10]. This higher prevalence of smoking among men also explains part of the discrepancy in incidence between men and women [11]. Despite the reduction in exposure to some risk factors, significant exposure, and thus disease, remains. This means that the burden on the health care system will remain substantial especially when considering that at least 50 % of bladder cancers recur [12] and long-term monitoring of patients is required, resulting in the highest per patient lifetime costs amongst all cancers [13]. For example, in the US, the annual cost of care of bladder cancer was estimated to be $US4 billion. Therefore, primary prevention is paramount, particularly because many of the risk factors are modifiable and therefore preventable.
Prioritising control measures should be evidence-based. To this end, an accessible and comprehensive overview is needed of the modifiable risk factors in the development of bladder cancer, including estimates of public health impact. To our knowledge, no quantitative overview has been published addressing all modifiable risk factors of bladder cancer. Therefore, our aim was to give an overview of the current state of knowledge, at the highest level of evidence, with regard to modifiable lifestyle, environmental, and occupational risk factors for development of bladder cancer by performing a systematic review of meta-analyses (MAs), in combination with a series of meta–meta-analyses (MMAs).

Methods

This systematic review was registered with PROSPERO (identification number CRD42015023411) [14]. Where relevant, the publication is written in accordance to the PRISMA guidelines [15].

Search strategy

A systematic literature search was performed up to September 2015 in PubMed, Embase, and the Cochrane database to identify published articles of MAs and pooled analyses describing the association between lifestyle, environmental, and occupational risk factors and the development of bladder cancer. In addition, PROSPERO was searched and authors of registered but not published reviews were contacted. Finally forward and backward referencing of relevant publications was checked for additional publications.
The database was searched using the following search terms: “urinary bladder neoplasms”[MeSH Terms], “urinary bladder neoplasms”[All Fields], “bladder cancer”, combined with systematic[sb], meta-analysis[Title/Abstract], meta-analysis[Publication Type], systematic review[Text Word], pooled analysis[Text Word].

Selection criteria for publications

A first screening was done based on the title and abstract. Articles were considered for inclusion if they were MAs or pooled analyses describing the association between modifiable risk factors and development of bladder cancer, written in English. Inclusion was limited to articles published from 1995, as during the 1990s systematic reviews and meta-analyses started to replace narrative reviews, and methods and terminology were well established by that time [16]. When the references could not be rejected with certainty, the full texts were obtained and a second screening was done. One article may report multiple MAs on different exposures.
The exposure of interest was any modifiable risk factor. ‘Modifiable’ was defined as a risk factor that is in any way reasonably modifiable, meaning that genetic and medical conditions were excluded as these are generally not modifiable. The outcome of interest was defined as incidence of bladder cancer as a binary outcome. Studies that included estimates based on prevalence or mortality were used as a proxy for incidence when estimates on incidence only were not available. Studies presenting results on genitourinary cancers without giving estimates for bladder cancer alone and studies reporting on urothelial cancer alone were excluded. Additionally, pooled risk estimates had to be presented with the accompanying 95 % confidence interval, accepted as odds ratio (OR), risk ratio (RR), hazard ratio (HR), standardised incidence ratio (SIR), or effect size (ES) if the latter consisted of a combination of the previously mentioned ratios. For the purpose of this paper, these estimates are all referred to as relative risks (RR).

Data extraction

Data was extracted by AA and all entries were double-checked completely for errors by KS. Any disagreement was discussed between the review authors until consensus was reached. When needed, authors of publications were contacted for additional information.
For each article, the following data was extracted when available: first author, year of publication, journal, risk factor(s) studied, number of events, types of studies included, number of studies included, type of risk estimate (OR, RR, SIR), outcome variable (incidence, prevalence, mortality, or combination), and per MA (statistical procedure): the exposures that were compared, the risk estimate and the 95 % confidence interval, a measure of heterogeneity, the number of primary studies included, and a measure of publication bias.

Selection criteria for estimates

The estimates to be included had to be based on a minimum of two primary studies. They were selected based on the following list of decisions, and in this order: (1) bladder cancer only over urothelial cancers, (2) overall estimates over sub-group estimates, (3) more adjusted estimates over less adjusted estimates, (4) smoking adjusted over other adjustments, (5) incidence over prevalence or mortality, (6) random effects model over fixed effects model, and (7) pooling of cohort studies over pooling of case–control or cross-sectional studies.

Synthesis of results

If only one article was available on a specific risk factor, these estimates were included directly. If multiple articles were available, we selected the most comprehensive MA. This could occur in one of two ways. (1) The preferred method was to combine two MAs in a MMA to obtain an overall estimate based on the largest number of studies. However, we considered this only appropriate if the level of overlap between the primary studies included in each publication was no more than 50 %, measured as the percentage of studies of the smaller publication that overlapped with those of the larger publication. In addition, the exposure categories had to be comparable enough to be combined. (2) If, by following this rule, it was not possible to combine publications, the most comprehensive publication was included, based on the largest number of included primary studies. Basing this on the largest number of studies, rather than the largest sample size, was done because it was often not possible to determine the publication with the largest sample size due to insufficient data in the publication.
MMA was performed using a random-effects model. Heterogeneity was assessed between the included MAs using the I2 statistic [17]. All statistical analyses were carried out in STATA V13.0 software and p values of 0.05 or below, or a confidence level of 95 %, were considered statistically significant.
In order to provide a measure of public health impact, a probability of causation [18] (POC) was calculated for those risk estimates that were found to be significantly associated with the risk of bladder cancer. In addition, a combined POC [18] was calculated for the lifestyle factors that one can be exposed to at one time. Careful attention was paid to avoid overlapping exposures, such as vitamin C intake, and fruit and vegetable consumption. In that case the most all-inclusive factor was included. No such combined estimate was calculated for all occupational factors combined, as one will unlikely be exposed to multiple occupations at one time.
POC can be interpreted as the percentage of exposed cases that are attributable to the exposure (e.g. the number of cases among smokers that are attributable to smoking). In case of a protective factor this should be read as the proportion of non-exposed cases that are attributable to the fact that they are non-exposed (e.g. the number of cases among people with low fruit and vegetable intake that are attributable to the low fruit and vegetable intake).

Role of the funding source

The funding body was not involved in the study design; in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Results

Figure 1 shows the literature search and selection process. A total of 1,496 articles were identified, from which 126 articles were selected based on the title and abstract for further evaluation. Of these, 32 articles were excluded (Appendix 1) for the following reasons: not being a MA, bladder cancer estimates were not reported separately from other urinary cancers, no risk estimate reported, or only mortality estimates were reported. Furthermore, 12 articles were excluded because all included primary studies were also part of a larger MA or because an update was available. This resulted in a total of 82 eligible articles (Appendix 2). Of these 82 articles, 21 articles were selected as the most comprehensive MA for a single risk factor, and five articles were combined in two MMAs, together reporting results for 36 risk factors. The statistically significant results from all most comprehensive MAs, totalling 19 lifestyle factors and 48 occupational factors, are summarised in Table 1 and illustrated in Figs. 2 and 3, for the increased and decreased risks respectively.
Table 1
Modifiable risk factors with statistically significant association with bladder cancer
Risk factor
Total MAs
Total primary studies
Total BC cases in specific MA
Outcome type
Comparison
Relative risk (95 % CI)
Confidence interval
POC (%)
Combined POC (%)
Lifestyle factors
Fruit and vegetable consumption [19]
1
10
 
NS
High versus low intake
0.81
0.67–0.99
19
$
Fruit consumption [19]
1
21
9867
NS
High versus low intake
0.77
0.69–0.87
23
 
Citrus fruit [20]
1
14
7372
Incidence
High versus low intake
0.85
0.76–0.94
15
 
Vegetable consumption [19, 21]
2 (MMA)
31 unique; 3 duplicate
8808 unique; 765 duplicate
NS
High versus low intake
0.83
0.75–0.92
17
 
Cruciferous vegetable [19]
1
11
6496
NS
High versus low intake
0.84
0.77–0.91
16
 
Processed meat [33]
1
11
7562
NS
High versus low intake
1.22
1.04–1.43
18
$
Vitamin A [36]
1
11
4990
NS
High versus low intake (dietary and supplements) and blood levels
0.82
0.65–0.95
18
 
Vitamin A supplement [36]
1
5
1403
Incidence
Supplementation versus placebo or no supplementation
0.64
0.47–0.82
36
 
Vitamin D [39]
1
5
2238
Incidence/mortality
High versus low serum level
0.75
0.65–0.87
25
 
Vitamin E [38]
1
15
5224
Incidence
High versus low intake
0.82
0.74–0.90
18
 
Folate [41]
1
13
6280
Incidence
High versus low intake
0.84
0.72–0.96
16
 
Selenium [42]
1
7
1014
Incidence
High versus low serum or toenail level
0.61
0.42–0.87
39
 
Antioxidant supplement [44]
1
4
NR
Incidence
Supplementation versus placebo or no supplementation
1.52
1.06–2.17
34
 
Obesity [46]
1
12
 
NS
Obese versus normal body weight
1.10
1.03–1.18
9
 
Cigarette smoking [10]
1
13
9129
Incidence
Current cigarette smokers versus never smokers
3.14
2.53–3.75
68
$
 
1
12
8659
Incidence
Former cigarette smokers versus never smokers
1.83
1.52–2.14
45
 
Pipe smoking [52]
1
6
34
Incidence
Pipe only smokers versus never smokers
1.90
1.2–3.1
47
 
Cigar smoking [52]
1
6
52
Incidence
Cigar only smokers versus never smokers
2.30
1.6–3.5
57
 
Physical activity [56]
1
7
NR
Incidence
High versus low
0.86
0.77–0.95
14
$
Combined POC
81.8
Occupational factors [61]
Tobacco workers
1
3
87
Incidence
Versus any other occupation
1.72
1.37–2.15
42
 
Dye workers
1
21
344
Incidence
Versus any other occupation
1.58
1.32–1.90
37
 
Chimney sweeps
1
4
146
Incidence
Versus any other occupation
1.53
1.30–1.81
35
 
Nurses
1
13
1195
Incidence
Versus any other occupation
1.49
1.06–2.08
33
 
Rubber workers
1
45
1263
Incidence
Versus any other occupation
1.49
1.37–1.61
33
 
Waiters
1
9
1146
Incidence
Versus any other occupation
1.43
1.34–1.52
30
 
Aluminium workers
1
21
977
Incidence
Versus any other occupation
1.41
1.29–1.55
29
 
Hairdressers
1
47
1445
Incidence
Versus any other occupation
1.32
1.24–1.40
24
 
Printers
1
42
1724
Incidence
Versus any other occupation
1.23
1.17–1.30
19
 
Seamen
1
10
1791
Incidence
Versus any other occupation
1.23
1.17–1.29
19
 
Oil and petroleum workers
1
17
637
Incidence
Versus any other occupation
1.20
1.06–1.37
17
 
Shoe and leather workers
1
39
1091
Incidence
Versus any other occupation
1.20
1.12–1.29
17
 
Plumbers
1
8
1418
Incidence
Versus any other occupation
1.20
1.14–1.27
17
 
Sales agents
1
91
11923
Incidence
Versus any other occupation
1.17
1.15–1.20
15
 
Artistic workers
1
34
1678
Incidence
Versus any other occupation
1.16
1.10–1.22
14
 
Cooks and stewards
1
15
1117
Incidence
Versus any other occupation
1.15
1.08–1.22
13
 
Chemical process workers
1
79
3712
Incidence
Versus any other occupation
1.14
1.10–1.19
12
 
Metal workers
1
62
5461
Incidence
Versus any other occupation
1.14
1.11–1.18
12
 
Drivers
1
57
10396
Incidence
Versus any other occupation
1.14
1.11–1.16
12
 
Fishermen
1
7
1525
Incidence
Versus any other occupation
1.13
1.08–1.19
12
 
Painters
1
43
3472
Incidence
Versus any other occupation
1.13
1.09–1.17
12
 
Assistant nurses
1
2
812
Incidence
Versus any other occupation
1.12
1.04–1.20
11
 
Domestic assistants
1
35
1776
Incidence
Versus any other occupation
1.12
1.07–1.18
11
 
Launderers and dry cleaners
1
19
767
Incidence
Versus any other occupation
1.12
1.04–1.21
11
 
Public safety workers–police
1
30
2382
Incidence
Versus any other occupation
1.11
1.07–1.16
10
 
Physicians
1
10
858
Incidence
Versus any other occupation
1.11
1.03–1.19
10
 
Clerical workers
1
148
21109
Incidence
Versus any other occupation
1.11
1.10–1.13
10
 
Electrical workers
1
45
5314
Incidence
Versus any other occupation
1.11
1.07–1.14
10
 
Military personnel
1
14
2091
Incidence
Versus any other occupation
1.11
1.05–1.18
10
 
Mechanics
1
127
67195
Incidence
Versus any other occupation
1.11
1.09–1.13
10
 
Smelting workers
1
24
2319
Incidence
Versus any other occupation
1.11
1.06–1.16
10
 
Transport workers
1
35
5243
Incidence
Versus any other occupation
1.10
1.06–1.13
9
 
Glass makers, etc.
1
29
2219
Incidence
Versus any other occupation
1.10
1.05–1.15
9
 
Textile workers
1
79
3822
Incidence
Versus any other occupation
1.10
1.06–1.14
9
 
Waiters and bartenders
1
34
1179
Incidence
Versus any other occupation
1.10
1.01–1.19
9
 
Building caretakers
1
4
3246
Incidence
Versus any other occupation
1.09
1.06–1.13
8
 
Health care workers
1
20
1072
Incidence
Versus any other occupation
1.09
1.06–1.12
8
 
Food manufacturing workers
1
33
3559
Incidence
Versus any other occupation
1.08
1.04–1.12
7
 
Postal workers
1
4
1791
Incidence
Versus any other occupation
1.08
1.03–1.13
7
 
Packers, loaders, and warehouse workers
1
25
3586
Incidence
Versus any other occupation
1.08
1.04–1.13
7
 
Shop workers
1
4
6068
Incidence
Versus any other occupation
1.07
1.05–1.10
7
 
Technical workers, etc.
1
37
11579
Incidence
Versus any other occupation
1.04
1.02–1.06
4
 
Economically inactive
1
2
23436
Incidence
Versus any other occupation
0.96
0.95–0.97
4
 
Religious and legal workers, etc.
1
6
1754
Incidence
Versus any other occupation
0.93
0.88–0.97
7
 
Forestry workers
1
53
10865
Incidence
Versus any other occupation
0.88
0.86–0.90
12
 
Teachers
1
30
3884
Incidence
Versus any other occupation
0.85
0.82–0.87
15
 
Gardeners
1
10
3308
Incidence
Versus any other occupation
0.78
0.75–0.81
22
 
Farmers
1
73
16607
Incidence
Versus any other occupation
0.69
0.68–0.71
31
 
BC bladder cancer, MA meta-analysis, MMA meta-meta-analysis, NS not specified, POC probability of causation
$Risk factors and protective factors that have been included in the combined POC. The POC can be interpreted as the proportion of exposed cases that are attributable to the exposure

Lifestyle factors

Four general topics emerged from the literature search with regard to lifestyle: dietary factors, consumption of tobacco, alcohol consumption, and physical activity.

Dietary factors

Fruit and vegetable
The MA by Yao et al. [19] was selected as the most comprehensive publication for overall fruit and vegetable intake and reported significant protective effect on bladder cancer (RR 0.81; 95 % CI 0.67–0.99; I2 = 58.4 %; n = 10).
Fruit only
MA by Yao et al. [19] was selected as most comprehensive for consumption of overall fruit and the MA by Liang et al. [20] for intake of citrus fruit (e.g. oranges, lemons, limes, and grapefruits;). Overall fruit was associated with a reduced risk of bladder cancer (RR 0.77; 95 % CI 0.69–0.87; I2 = 54.9 %; n = 27) as were citrus fruit (highest vs. lowest intake: RR 0.85; 95 % CI 0.76–0.94; I2 = 72.1 %; n = 14). Yao et al. [19] reported significant publication bias for overall and citrus fruit intake.
Vegetables only
By pooling results from Yao et al. [19] and Steinmaus et al. [21] in a MMA, the most comprehensive estimate could be obtained for overall vegetable consumption (n = 31 unique and n = 3 duplicate primary studies). The MA by Yao et al. [19] was selected as the most comprehensive publication for cruciferous vegetables. Consumption of overall vegetables (RR 0.83; 95 % CI 0.75–0.92; I2 = 0.0 %; n = 21 + 8) and cruciferous vegetables specifically (RR 0.84; 95 % CI 0.77–0.91; n = 11), resulted in a reduced risk of bladder cancer.

Total fluid

Bai et al. [22] was the most comprehensive estimate and found no statistically significant association between total fluid intake and bladder cancer (RR 1.12; 95 % CI 0.94–1.33; I2 = 82.8 %; n = 14).

Tea

The MA by Qin et al. [23] was selected as most comprehensive and they found a significant protective effect for black tea consumption (RR 0.79; 95 % CI 0.59–0.99; I2 = 33.1 %; n = 7) but not for overall and green tea consumption.

Coffee

Six MAs [2428] reported on the association between coffee consumption and bladder cancer risk, of which Villanueva et al. [27], Yu et al. [26], and Wu et al. [29] could be combined into a single estimate to provide the most comprehensive estimate (n = 38 unique and n = 3 duplicate primary studies). No statistically significant association was observed, with substantial heterogeneity (RR 1.12; 95 % CI 0.80–1.44; I2 = 94.2 %; n = 18 + 9 + 6).

Sweetened carbonated beverages

Only one MA by Boyle et al. [30] was identified, reporting on the association between sweetened carbonated beverage consumption and risk of bladder cancer. No statistically significant association was found (RR 1.13; 95 % CI 0.89–1.45; n = 5).

Milk and dairy products

As reported by Mao et al. [31], which was selected as most comprehensive, overall milk, skim milk, and fermented milk were associated with a significantly reduced incidence of bladder cancer (milk: RR 0.84; 95 % CI 0.72–0.97; I2 = 70.1 %; n = 16; skim milk: RR 0.47; 95 % CI 0.18–0.79; I2 = 0; n = 2; fermented milk: RR 0.69; 95 % CI 0.47–0.91; I2 = 62.5; n = 5). In contrast, consumption of whole milk was associated with a significantly increased risk of bladder cancer (RR 2.23; 95 % CI 1.45–3.00; I2 = 0; n = 2).

Fish

The MA by Li et al. [32] was the only MA that studied the association between fish consumption and bladder cancer and reported no statistically significant association (RR 0.86; 95 % CI 0.61–1.12).

Meat

The MA by Li et al. [33] was selected as most comprehensive and they found an increased risk of bladder cancer associated with processed meat (RR 1.22; 95 % CI 1.04–1.43; n = 11) but not with red meat (RR 1.15; 95 % CI 0.97–1.36; n = 14).

Alcohol

The MA by Pelucchi et al. [34] was considered most comprehensive and they found no statistically significant association for heavy drinkers (≥ 3 drinks (≥ 37.5 g)/day; RR 0.97; 95 % CI 0.72–1.31; n = 7) or moderate drinkers (<3 drinks/day; RR 0.98; 95 % CI 0.89–1.07; n = 15).

Egg

The MA by Li et al. [35] was the only MA identified in which no significant association was detected for overall egg consumption (RR 1.11; 95 % CI 0.73–1.69; n = 6). However, when looking at cooking methods, an increased risk of bladder cancer was found for fried egg (RR 2.04; 95 % CI 1.41–2.95; n = 2) but not for boiled egg (RR 1.25; 95 % CI 0.82–1.91; n = 2).

Vitamin A: body levels, intake, and supplementation

The MA by Tang et al. [36] was selected as most comprehensive MA for both overall intake and body levels of vitamin A, and vitamin A supplementation. They found a significantly lower risk of bladder cancer among individuals with higher dietary intake or higher blood levels of vitamin A (RR 0.82; 95 % CI 0.65–0.95; I2 = 46.3 %; n = 11). When looking only at intake of vitamin A, the association was significantly protective for vitamin A supplementation, consisting of beta-carotene, and/or retinol supplementation (highest vs. lowest: RR 0.64; 95 % CI 0.47–0.82; I2 = 0 %) but not for dietary intake (highest vs. lowest: RR 0.90; 95 % CI 0.80–1.01; I2 = 0 %).
Jeon et al. [37] investigated the effect of only beta-carotene supplementation (so not retinol), compared to no supplementation, and found an increased risk of bladder cancer (RR 1.52; 95 % CI 1.03–2.24; I2 = 0.0 %; n = 2).

Vitamin C

The MA by Wang et al. [38] was the only MA studying the association between vitamin C intake and bladder cancer. Combining vitamin C intake from diet and supplementation, they found a marginally significantly decreased risk of bladder cancer (RR 0.90; 95 % CI 0.79–1.00; I2 = 43.7 %; n = 20).

Vitamin D

The MA by Liao et al. [39] investigated only the role of vitamin D serum level. They found that the risk of bladder cancer was decreased among individuals with the highest levels of serum vitamin D (RR 0.75; 95 % CI 0.65–0.87; n = 5). The MA by Chen et al. [40] reported on the role of vitamin D intake from diet and supplements. Combining vitamin D intake from diet and supplementation, they found no significantly altered risk of bladder cancer (RR 0.92; 95 % CI 0.66–1.28; n = 3).

Vitamin E

The MA by Wang et al. [38] was selected as the most comprehensive MA and reported significantly reduced risk of bladder cancer for vitamin E intake (RR 0.82; 95 % CI 0.74–0.90; I2 = 0 %; n = 15).

Folate

The association between folate intake and risk of bladder cancer was studied only in a MA by He et al. [41]. They found a significantly reduced risk of bladder cancer (RR 0.84; 95 % CI 0.72–0.96; I2 = 28.9 %; n = 13). The association remained significantly reduced when pooling studies on dietary folate only (RR 0.82; 95 % CI 0.65–0.99; I2 = 57.9 %; n = 9), but not on supplemental folate only (RR 0.91; 95 % CI 0.58–1.25; I2 = 62.6 %; n = 3).

Selenium: body levels and supplementation

Two MAs [42, 43] were identified studying the association between selenium levels in the body, measured in serum or toenail, and bladder cancer. Amaral et al. [42] was selected as the most comprehensive MA. They found that the risk of bladder cancer was significantly lower among individuals with the highest selenium levels in the body (RR 0.61; 95 % CI 0.42–0.87; n = 7).
Selenium supplementation was studied in one MA by Vinceti et al. [43]. They meta-analysed two RCTs and found no statistically significant association (RR 1.14; 95 % CI 0.81–1.61; n = 2).

Antioxidant supplementation

One MA by Myung et al. [44] reported on multiple types of antioxidant supplementation together, studied in RCTs. They found that antioxidant supplementation significantly increased the risk of bladder cancer (RR 1.52; 95 % CI 1.06–2.17; I2 = 0.0 %; n = 4).

Dietary acrylamide

The association between dietary acrylamide intake and bladder cancer was studied in one MA, authored by Pelucchi et al. [45] They reported no statistically significant association (RR 0.93; 95 % CI 0.78–1.11; n = 3).

Obesity

Two MAs [46, 47] reported on the association between body weight and bladder cancer. The MA by Sun et al. [46] was selected as most comprehensive. They found an increased risk of bladder cancer among obese individuals (BMI ≥ 30; RR 1.10; 95 % CI 1.03–1.18; I2 = 8.8 %; n = 12) but not among pre-obese individuals (BMI 25.00–29.99; RR 1.07; 95 % CI 0.99–1.16; I2 = 46.1 %; n = 13).

Consumption of tobacco

Active smoking
Eight MAs [10, 11, 4853] were identified on the effect of active smoking of tobacco on the risk of bladder cancer. With regard to cigarette smoking, Cumberbatch et al. [53] and Van Osch et al. [10] both included almost the same number of primary studies: n = 90 versus n = 89 respectively. Although theoretically this meant that the paper by Cumberbatch et al. would be most comprehensive, after discussion between the authors, the paper by Van Osch et al. was selected as most comprehensive as they reported dose–response analyses on duration, intensity, and time since cessation of smoking. Because smoking was already known to be the most important modifiable risk factor of bladder cancer, the dose–response variables were considered valuable additional information. It must be noted that calculated risks do not differ much between both MAs (Appendix 2).
Van Osch et al. [10] reported a significantly increased risk of more than 3 times in current smokers (RR 3.14; 95 % CI 2.53–3.75) and almost 2 times in former smokers (RR 1.83; 95 % CI 1.52–2.14). Their dose–response associations showed a positive trend with increasing intensity of smoking and number of pack years, reaching a plateau from about 15 cigarettes/day and 50 pack-years. Increasing duration since cessation of smoking resulted in a reducing risk, although former smokers remained at a 50 % increased risk even after more than 20 years of cessation.
Hemelt et al. [11] also reported on the risk among smokers of any type of tobacco. They found an increased incidence of bladder cancer among current smokers (RR 3.35; 95 % CI 2.90–3.88; n = 11) as well as among ever-smokers (RR 2.25; 95 % CI 1.96–2.59; n = 15).
Two MAs [52, 53] additionally reported on the effect of pure cigar and pure pipe smoking. Pitard et al. [52] was considered most comprehensive and they reported a significantly increased risk of bladder cancer among both pipe smokers (RR 1.9; 95 % CI 1.2–3.1; n = 6) and cigar smokers (RR 2.3; 95 % CI 1.6–3.5; n = 6).
Passive smoking
Van Hemelrijck et al. [54] reported on the association between passive smoking and bladder cancer. They found no statistically significant association in individuals exposed to passive smoking (RR 0.99; 95 % CI 0.86–1.14; I2 = 35.6 %; n = 8) compared to never-smoking individuals with no exposure to passive smoking.
Smokeless tobacco
Use of smokeless tobacco, including chewing tobacco, oral snuff, and unspecified smokeless tobacco, was studied in two MAs [53, 55]. Lee et al. [55] was considered most comprehensive. No statistically significant association was found with development of bladder cancer (RR 0.95; 95 % CI 0.71–1.29; n = 9).

Physical activity

Keimling et al. [56] wrote the only MA on the association between physical activity and bladder cancer. They found a statistically significant protective effect on the bladder cancer risk among individuals with the highest levels of physical activity (RR 0.86; 95 % CI 0.77–0.95; n = 7).

Personal hair dye use

Turati et al. [57] updated previous MAs [5860] to investigate the association between personal use of hair dye and bladder cancer. They found no statistically significant increased risk among users of personal hair dye (smoking adjusted RR 0.94; 95 % CI 0.82–1.08; n = 12).

Occupational factors

Multiple MAs were identified on the association between occupational factors and bladder cancer. Most MAs reported on a single occupation or occupational group, or a single specific occupational exposure (Appendix 2). Moreover, four MAs [6164] reported on a large number of occupational categories. Cumberbatch et al. [61] and Reulen et al. [62] authored two large MAs on different occupations based on 217 and 130 different studies respectively, whereas Kogevinas et al. [63] and ‘t Mannetje et al. [64] both did a pooled analysis of eleven case–control studies conducted in European countries reporting results for men and women, respectively. The paper by Cumberbatch et al. was considered the most comprehensive for all identified occupations based on the number of studies included. They found the following occupations to have a statistically significant increased risk of more than 20 %: tobacco workers, dye workers, chimney sweeps, nurses, rubber workers, waiters, aluminium workers, hairdressers, printers, seamen, oil and petroleum workers, shoe and leather workers, and plumbers. Protective effects were found for farmers, gardeners, teachers, forestry workers, religious and legal workers, and economically inactive workers. Statistically significant associations reported by Cumberbatch et al. are listed in Table 1. All other associations are summarized in Appendix 3 along with findings by Reulen et al. [62], Kogevinas et al. [63], and ‘t Mannetje et al. [64].

Probability of causation

The estimates for probability of causation (POC), displayed in percentages, are presented in Table 1. The percentages ranged from 9 to 68 % among the lifestyle factors, and between 4 and 42 % for the occupational exposures. The four highest POCs are found among the smoking estimates: 68 % of the bladder cancer incidence among cigarette smokers, 57 % among cigar smokers, 47 % among pipe smokers and 45 % among former cigarette smokers can be attributed to this habit.
A POC was calculated for four factors combined, which were considered sufficiently independent: total fruit and vegetable consumption, processed meat consumption, smoking, and physical activity. To avoid overlap, the only estimate included for smoking was for cigarette smoking as most smokers are (also) cigarette smokers (78.7 %) and only 4.5 % was found to be pure pipe and/or cigar smoker [52]. The combined POC showed that up to 81.8 % of the bladder cancer cases, among those with non-optimal lifestyle behaviours, could be prevented through lifestyle modifications.

Discussion

In total, 12 lifestyle factors and 48 occupational factors emerged that significantly increased or decreased the risk of bladder cancer. Such numerous modifiable risk factors present an opportunity and great potential for prevention. Below, the significantly associated risk factors will be discussed.

Smoking

The most important risk factor proved to be smoking, particularly the risk was highest for current smokers of cigarettes (RR 3.14), [10] but also for smokers of cigars only (RR 2.3) and pipes only (RR 1.9) [52]. An interesting finding was that a plateau was reached at about 15 cigarettes/day, meaning that heavier smoking does not carry a much higher risk than less heavy smoking [10]. Although the risk slowly decreased with longer cessation of cigarette smoking, the RR was still 50 % increased 20 years of cessation.
Characteristics of the tobacco smoked may influence this association. In previous studies, individuals smoking black tobacco had a higher risk compared to smokers of blond tobacco, due to the higher concentrations of carcinogens in black tobacco [6571]. Also, inhalation of the tobacco smoke into the lungs and throat resulted in a higher risk compared to inhalation only into the mouth, [49, 65, 7176] although not all evidence supports this [7780].
Tobacco smoke contains numerous carcinogens that contribute to the initiation and promotion of tumour development. These chemicals are renally excreted, making it directly toxic to the human urinary bladder. During metabolisation of these compounds, DNA-adducts are formed, leading to permanent genetic mutations. If this occurs in an oncogene or tumour suppressor gene, it may result in uncontrolled growth and eventually cancer.
Genetic mutations, such as NAT2 slow acetylation and GSTM null genotypes, have previously been shown to be associated with increased susceptibility to cancer [3]. The enzymes for which the genes code play a role in the detoxification pathways of i.a. aromatic amines and PAHs. These mutations do not intrinsically cause bladder cancer but do increase susceptibility when exposed to tobacco smoke or other sources of exposure [81, 82].

Dietary factors

Because the metabolites of many food groups are excreted by the urinary tract, dietary factors have often been suggested and researched as risk factors of bladder cancer [83]. Several different nutritional factors have been identified, showing both increased and decreased risks of bladder cancer.

Fruit, vegetables, and antioxidants

One key group of foods that was associated with a lower risk of bladder cancer were fruits and vegetables. Besides these groups as a whole, intake of both citrus fruit and cruciferous vegetables were researched. The effect is suggested to be due to the vitamins, minerals, and phytochemicals that fruit and vegetables contain, which have antioxidant properties [84, 85]. Antioxidants may protect against cancer through inhibition of oxidation of DNA, controlling of cell proliferation and apoptosis [85], and facilitation of metabolisation of carcinogenic compounds into less toxic substances, although the association may be dose-dependent [86].
It should be noted that significant publication bias was found in the MA on overall and citrus fruit consumption [19]. Because small studies with negative results tend not to be published, the effect size found in the MAs on these risk factors may actually be attenuated.
The MAs included in our review that studied vitamins separately, came to supporting conclusions. For all but vitamin C, higher intakes were associated with a significantly reduced risk of bladder cancer, with effects on −39 % for selenium, −18 % for vitamin A and E, and −16 % for folate.
Vitamin A intake was found to be negatively associated with bladder cancer when data on dietary intake, supplementation, and blood levels were combined. However, when studied by intake source separately, the protective effect was only found for vitamin A supplementation but not for dietary intake [36]. Furthermore results on supplementation were not consistent as Jeon et al. [37], found a significantly increased risk of bladder cancer of 52 % among participants taking supplementation in experimental studies. These conflicting results may be the result of a dose-dependent relationship, showing intake to be protective at low doses and harmful at high doses. Another explanation may be the different study design, in which the reduced risk found in observational studies may actually be the effect of an overall healthier lifestyle, as those individuals who choose to use nutritional supplementation tend to have a healthier lifestyle overall [87], Vitamin A plays an important role in cell proliferation and differentiation [88], and carotenoids can directly affect carcinogenesis through their antioxidant properties, or indirectly after transformation of provitamin A carotenoids into vitamin A [89, 90].
Vitamin E consists of a group of lipid soluble molecules, including four tocopherols and four tocotrienols. Specifically γ-tocopherol, δ-tocopherol, and tocotrienols inhibit several inflammatory pathways, [91] which is important because chronic inflammation or chronic infection influences development and progression of cancer, [92] In addition, vitamin E is a potent lipid-soluble antioxidant, inhibiting lipid peroxidation and thereby protecting cell membranes from peroxidative damage [93].
Although higher levels of selenium protected against bladder cancer, causation could not be confirmed through supplementation intervention [42], The specific mechanism of action of selenium in carcinogenesis is not yet well understood. Several theories have been suggested, including selenoproteins serving as antioxidants and metabolites of selenium involved in redox cycling, modification of protein thiols, and methionine mimicry [94].
However, despite these suggested protective properties of antioxidants, analysis of multiple types of antioxidant supplementation together, showed a 52 % increased risk of bladder cancer [44]. An explanation for this discrepancy may be that it is not one antioxidant alone that has cancer-preventative properties, but rather the interaction between multiple antioxidants and other phytochemicals, such as it occurs with consumption of a diet rich in fruit and vegetables.

Other nutrients and food groups

Because consumption of processed meat but not red meat was associated with bladder cancer, the effect may result from different forms of mechanical, chemical, and enzymatic treatment that processed meat has been exposed to. One hypothesis suggests that nitrite, which is used as a colour and flavour preservative in processed meat, combines with secondary amines from proteins to form nitrosamines that are found to be carcinogenic to, amongst other organs, the bladder [95]. Although red and processed meat are often studied in relation to disease development, particularly cancer, the exact mechanism of action is still unclear and is likely to be a combination of factors present in or associated with meat consumption [96, 97].
The protective effect of folate, a vitamin predominantly found in vegetables, is suggested to be through its role in DNA synthesis, repair, and methylation [98]. In previous research, low levels of folate were associated with hypomethylation of DNA resulting in dysregulation of proto-oncogenes and tumour suppressor genes, and therefore an increased risk of cancer [99]. However, the association is not as straightforward as may be expected. Research suggests that timing and dose of folate plays an important role in its effect on cancer development [100]. Because folate plays a role in de-novo synthesis of nucleotides, it will support healthy tissue and prevent tumour development. However, once pre-neoplastic lesions have been established, it will also support these rapidly proliferating tissues resulting in rapid tumour progression.
In line with previous findings for colorectal cancer [101] and breast cancer, [102] higher serum vitamin D was found to be protective against bladder cancer. Calcitriol, the potent hormone produced in the body from vitamin D, plays a role in multiple stages of cancer development, through both genomic and non-genomic pathways [103]. No association was found for dietary and supplemental intake of vitamin D, which may result from dietary intakes not adequately reflecting calcitriol available to the body as it is also endogenously formed in response to UV-light.
Previous reviews have also mentioned other dietary factors increasing the risk of bladder cancer, among which higher intake of soy, fat, barbecued meats, and artificial sweeteners [84, 104]. However, no MAs were identified on these factors so these factors have not been included in our overview.

Fluid intake and water contaminants

Whereas increased intake of fluids dilutes urine and increases micturition, leading to a reduced exposure of the bladder to carcinogens, it may also increase exposure when the fluid itself contains carcinogens [3]. For example, increased risk of bladder cancer was found with water chlorination [105, 106] and arsenic contamination [107, 108]. However, no significant association was found for either all fluid intake or water specifically [22]. Together, this is in line with the suggested dual effect of increased fluid intake on bladder cancer risk.

Physical activity

Physical activity was found to have a small but significant protective effect against bladder cancer. The effect found was not modified by BMI or smoking, as the authors explain in their MA [56]. Although the exact mechanism through which physical activity protects against cancer is not yet known, several mechanisms have been suggested acting on both tumour initiation and progression. These potential mechanisms include modification of carcinogen activity, and enhancement of antioxidant and DNA repair processes [109].

Occupation and occupational exposure to chemicals

Occupational factors are considered the second most important risk factor for bladder cancer after smoking [3, 110]. Over the years, many carcinogens have been identified by the IARC as definitely (group 1) or probably carcinogenic (group 2a). Occupational exposure to these carcinogens has been largely controlled and workers are now exposed to weaker carcinogens. The results of the MA by Cumberbatch et al. [53] show multiple occupations or occupational exposures that are significantly associated with the risk of bladder cancer.
Particularly workers exposed to aromatic amines, PAH, tobacco and tobacco smoke, combustion products, and heavy metals are at an increased risk. However, these findings will not be further discussed and repeated here as the MA by Cumberbatch et al. [61] offers an interesting and elaborate discussion on the matter. They also attempted to study a change in occupational risk over time but were limited by heterogeneity and small sample sizes.
Interestingly, farmers, gardeners, teachers, and forestry workers were found to be at a significantly lower risk. Farmers have been studied numerous times with regard to disease risk and have been suggested to be at both an increased and decreased risk of bladder cancer. It is thought of as a risk factor due to the exposure to chemicals such as pesticides, viruses, and other exposures. Although an increased risk was found in association with exposure to some pesticides, the evidence is not conclusive [111]. Both the European Food Safety Authority (EFSA) [112] and the IARC [113] did not find sufficient evidence to support carcinogenicity of pesticides. On the other hand, farmers, and possibly also gardeners and forestry workers, often have higher physical activity levels and fruit and vegetable consumption, as well as a lower prevalence of smoking [111].
Finally, in addition to exposure to carcinogens on an occupational basis, an increased risk of bladder cancer in certain occupational groups may also be the result of fewer possibilities for micturition during working hours. This may apply to, for example, sales workers, professional drivers, or other occupations where bathroom visits are limited to break times.

Public health impact

The calculated POCs show that by adopting the right lifestyle, while considering harmful environmental and occupational exposures, a large proportion of the burden of bladder cancer could be prevented. Particularly for smoking the POC was high, highlighting that smoking cessation and prevention of smoking initiation should remain high on the agenda. In addition, a diet rich in fruit and vegetables, particularly citrus fruit and cruciferous vegetables, and low in processed meat should be stimulated. Particularly working conditions involving exposure to aromatic amines, PAHs, tobacco and tobacco smoke, combustion products, and heavy metals should be given priority to reduce exposure to these compounds.

Limitations

The quality of a MA is strongly determined by the quality of the primary studies included. Not all studies corrected for smoking status, which is the most important risk factor for bladder cancer. The effects of this may be large, leading to an under- or overestimation of the true effect size. To minimise the effect of confounding in our study, only the most adjusted estimates from each MA were selected. Selection of the most comprehensive publication was based on the largest number of primary studies included, rather than the largest sample size. The latter would have been more desirable as the power of a study depends on it, but this data was often unavailable in the publications and number of studies included had to be used as a proxy. Results of MMA could be affected by duplicate inclusion of primary studies, leading to inflated precision and homogeneity [114]. Therefore, we minimised duplicate inclusion and performed a MMA only if at least 50 % of the included primary studies were ‘new’ in subsequent MAs.
The main limitation with regard to the combined POC is assumption of independence of risk factors. It is well known that lifestyle behaviours tend to cluster, [115] indicating that the factors are unlikely to be fully independent. Therefore, the combined POC is likely to be an overestimation and should be considered a maximum. However, the POCs of each of the individual factors are substantial, indicating that each plays an important part in the risk.
In this study, estimates of bladder cancer incidence were given priority over estimates of prevalence or mortality. Although the majority of included studies specified the outcome measure that was included or provided stratified results, not all did (Table 1). Because mortality and prevalence figures are greatly influenced by treatment success, this may have influence the estimates obtained.
Heterogeneity may always be an issue in MAs. Several of the studies included in the current review show moderate to high levels of heterogeneity. Whereas some identified study design, gender, or geographical region as possible source of heterogeneity [19, 22, 31], others could not find an explanation [20].
It should be noted that different classification criteria may be applied in studies to determine cases, including the TNM classification and stage grouping. Because any effect would be unlikely and small, this potential difference was not taken into consideration when selecting estimates.
This publication is a review of MAs. Additional risk factors for which no MA is available may prove to be of importance, but have not been included in this review. This study will help to identify gaps in knowledge with regard to MAs available.
It was our responsibility to give an objective and complete overview of the literature available. By using a protocol, including only MAs and by dealing appropriately with unexpected issues, we believe to have provided an overview of the risk factors associated with bladder cancer with high levels of objectivity and reliability.
In conclusion, the burden of bladder cancer could be significantly reduced through modification of lifestyle, environment, and occupational exposures. In fact, having numerous modifiable risk factors, among which multiple with a substantial RR, makes bladder cancer one of the most preventable diseases. Although substantial risks were found for, for example, smoking, some identified risk factors ‘only’ led to an increase or decrease of 10–15 %. This could be considered a minor effect, but reducing prevalence of a number of smaller risk factors together, could still result in significant overall risk reductions in the general population. Theoretically the included risk factors are, at least partially, modifiable. However, actually changing them is not always easily achieved, neither for one individual, let alone on a population level. Therefore, it is important that preventative and protective strategies pay attention to behaviour change in order to capture the greatest potential of risk reduction. When change is achieved, impact will not remain restricted to an improvement in the incidence of bladder cancer, as most of the included risk factors also play a role the risk of multiple other chronic diseases such as cancer or cardiovascular diseases, [116118] and deaths [119]. Since relapse of bladder cancer is common, future research may also elucidate whether the same risk factors play a role in prevention of bladder cancer relapse as they do in incidence.

Acknowledgments

This project was funded by the Maastricht University Interfaculty Programme ‘Eatwell’. The funder had no influence in the development and execution of this systematic review.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Unsere Produktempfehlungen

e.Med Interdisziplinär

Kombi-Abonnement

Für Ihren Erfolg in Klinik und Praxis - Die beste Hilfe in Ihrem Arbeitsalltag

Mit e.Med Interdisziplinär erhalten Sie Zugang zu allen CME-Fortbildungen und Fachzeitschriften auf SpringerMedizin.de.

e.Dent – Das Online-Abo der Zahnmedizin

Online-Abonnement

Mit e.Dent erhalten Sie Zugang zu allen zahnmedizinischen Fortbildungen und unseren zahnmedizinischen und ausgesuchten medizinischen Zeitschriften.

Anhänge

Appendix 1

See Table 2.
Table 2
List of meta-analyses identified for modifiable risk factors of bladder cancer
Risk factor
Identified meta-analyses
Included
Included for?
Reason exclusion
Diet
Fruit and vegetables
Riboli and Norat [120]
No
 
All primary studies are included in Yao et al. [19]
Liu et al. [121]
No
 
>50 % overlap
Vieira et al. [122]
No
 
>50 % overlap
Liu et al. [123]
No
 
>50 % overlap
Xu et al. [124]
No
 
>50 % overlap
Steinmaus et al. [21]
Yes
Vegetables (MMA)
 
Yao et al. [19]
Yes
Fruit and vegetables
Fruit
Vegetables (MMA)
Cruciferous vegetables
 
Liang et al. [20]
Yes
Citrus fruit
 
Tea
Zeegers et al. [125]
No
 
Include other urinary tract cancer
Zhang et al. [126]
No
 
>50 % overlap
Wu et al. [127]
No
 
>50 % overlap
Wang et al. [128]
No
 
>50 % overlap
Boehm et al. [129]
No
 
Not MA
Qin et al. [130]
Yes
Tea
 
Coffee
Arab [131]
No
 
Not MA
Pelucchi et al. [132]
No
 
Not MA
Huang et al. [24]
No
 
>50 % overlap
Sala et al. [28]
No
 
>50 % overlap
Zhou et al. [25]
No
 
>50 % overlap
Villanueva et al. [27]
Yes
Coffee (MMA)
 
Yu et al. [26]
Yes
Coffee (MMA)
 
Wu et al. [29]
Yes
Coffee (MMA)
 
Beverage consumption
Zeegers et al. [6]
No
 
Not MA
Boyle et al. [30]
Yes
Sweetened carbonated beverages
 
Milk
Zhang et al. [133]
No
 
Not MA
Lampe [134]
No
 
Not MA
Mao et al. [31]
No
 
>50 % overlap
Li et al. [135]
Yes
Milk
 
Fish
Li et al. [32]
Yes
Fish
 
Meat
Wang and Jiang [136]
No
 
Include urothelial cancer
Steinmaus et al. [21]
No
  
Li et al. [33]
Yes
Meat
 
Alcohol
Mao et al. [137]
No
 
Include urothelial cancer
de Menezes et al. 138]
No
 
Not MA
Bagnardi et al. [139]
No
 
>50 % overlap
Zeegers et al. [140]
No
 
>50 % overlap
Pelucchi et al. [34]
Yes
Alcohol
 
Egg
Fang et al. [141]
No
 
Include urothelial cancer
Li et al. [35]
Yes
Egg
 
Dietary acrylamide
Pelucchi et al. [34]
Yes
Dietary acrylamide
 
Vitamin A
Tang et al. [36]
Yes
Vitamin A
 
Steinmaus et al. [21]
No
  
Vitamin D
Liao et al. [39]
Yes
Serum level
 
Chen et al. [40]
Yes
Diet and supplement
 
Vitamin C & E
Wang et al. [38]
Yes
Vitamin C
Vitamin E
 
Chen et al. [40]
  
>50 % overlap
Folate intake
He and Shui [41]
Yes
Folate
 
Beta carotene supplement, Antioxidant supplement
Musa-Veloso et al. [142]
No
 
No MA for bladder cancer
Coulter et al. [143]
No
 
No MA for bladder cancer
Jeon et al. [37]
Yes
Beta-carotene supplements
 
Myung et al. [44]
Yes
Antioxidant supplement
 
Selenium
Amaral et al. [42]
Yes
Selenium levels in the body
 
Vinceti et al. [43]
Yes
Selenium supplementation
 
Omega-3 fatty acids
MacLean et al. [144]
No
 
No MA for bladder cancer
Zinc, Copper
Mao et al. [145]
No
 
No risk estimates reported
Olive oil
Psaltopoulou et al. [146]
No
 
No MA for bladder cancer
Fluid intake
Lotan et al. [147]
No
 
No MA
Stelmach and Clasen [148]
No
 
No MA
Villanueva et al. [27]
No
 
Included in Bai et al. [22]
Isa (submitted)
No
 
>50 % overlap
Bai et al. [22]
Yes
Total fluid intake
 
Obesity
Qin et al. [47]
No
 
>50 % overlap
Sun et al. [46]
Yes
Obesity
 
Behaviours
Smoking
Zeegers et al. [149]
No
 
Include other urinary tract cancer
Crivelli et al. [150]
No
 
Effect of smoking on prognosis of bladder cancer patients
Sasco et al. [151]
No
 
No MA
Zeegers et al. [6]
No
 
No MA
Vineis et al. [152]
No
 
No MA
Shiels et al. [153]
No
 
Not primary prevention of BC
‘t Mannetje et al. [154]
No
 
Discussed whether adjusting for smoking affects association between BC and occupation
Freedman et al. [49]
No
 
>50 % overlap
Brennan et al. [50]
No
 
>50 % overlap
Brennan et al. (Women) [51]
No
 
>50 % overlap
Hemelt et al. [11]
No
 
>50 % overlap
Puente et al. [48]
No
 
>50 % overlap
Cumberbatch et al. [53]
No
 
>50 % overlap
Van Osch et al. [10]
Yes
Cigarette smoking
 
Cigar and pipe
Pitard et al. [52]
Yes
Cigar and pipe
 
Passive smoking
Van Hemelrijck et al. [54]
Yes
Passive smoking
 
Smokeless tobacco
Lee et al. [55]
Yes
Smokeless tobacco
 
Waterpipe tobacco smoking
Akl et al. [155]
No
Waterpipe tobacco smoking
No MA, reporting one CC study
Physical activity
Keimling et al. [56]
Yes
Physical activity
 
Environmental
Personal hair dyes use
Kelsh et al. [58]
No
 
All primary studies were included by Turati et al. [57]
Takkouche et al. [60]
No
 
All primary studies were included by Turati et al. [57]
Huncharek et al. [59]
No
 
All primary studies were included by Turati et al. [57]
Rollison et al. [156]
No
 
No MA
Turati et al. [57]
Yes
Personal hair dyes use
 
Occupational
Various occupations
Cumberbatch et al. [61]
Yes
Various occupations
 
Various occupations
Reulen et al. [62]
No
 
Not the most comprehensive
Various occupations
Kogevinas et al. [63]
No
 
Not the most comprehensive
Various occupations
`t Mannetje et al. [64]
No
 
Not the most comprehensive
Painters
Bosetti et al. [157]
No
 
All primary studies are included by Bachand (2010)
Kogevinas et al. [63]
No
 
All primary studies are included by Bosetti et al. [157]
Guha et al. [158]
No
 
>50 % overlap
Bachand et al. [159]
No
 
Not the most comprehensive
Hairdresser
Kogevinas et al. [63]
No
 
All primary studies included by Takkouche et al. [160]
`t Mannetje et al. [64]
No
 
All primary studies included by Takkouche et al. [160]
Takkouche et al. [160]
No
 
>50 % overlap
Harling et al. [161]
No
 
Not the most comprehensive
Sales workers
Kogevinas et al. [63]
No
 
included in’t Mannetje et al. [160]
Mannetje et al. [162]
No
 
>50 % overlap
Motor vehicle driving
Kogevinas et al. [63]
No
 
Included in Manju, 2009
Boffetta and Silverman [163]
No
 
>50 % overlap
Manju et al. [164]
No
 
Not the most comprehensive
Farmers
Acquavella et al. [165]
No
 
Not the most comprehensive
Foundry workers
Gaertner RR, 2002 [166]
No
 
Not the most comprehensive
Textile workers
Mastrangelo et al. [167]
No
 
Not the most comprehensive
Flight attendants
Tokumaru et al. [168]
No
 
>50 % overlap
Buja et al. [169]
No
  
Petroleum industry
Wong et al. [170]
No
 
Mortality estimate only
Baena et al. [171]
No
 
Not the most comprehensive
Chemical workers
Greenberg et al. [172]
No
 
Not the most comprehensive
Dry cleaning
Vlaanderen et al. [173]
No
 
Not the most comprehensive
Inorganic lead compounds
Fu et al. [174]
No
 
Not the most comprehensive
Acrylonitrile workers
Cole et al. [175]
No
 
Included genitourinary cancers
Collins and Acquavella [176]
No
 
Not the most comprehensive
Polycyclic aromatic hydrocarbons
Bosetti et al. [177]
No
 
Updated in Rota et al. [179]
Boffetta et al. [178]
No
 
No MA
Rota et al. [179]
No
 
Not the most comprehensive
Metalworking fluids
Calvert et al. [180]
No
 
No MA
Perchloroethylene (Dry cleaning)
Mundt et al. [181]
No
 
No MA
Asbestos-exposed workers
Goodman et al. [182]
No
 
Mortality estimate only
CC case–control, MA meta-analysis, OR odds ratio

Appendix 2

See Table 3.
Table 3
Characteristics of meta-analyses investigating association between bladder cancer risk and various factors
References
Risk factor (s)
Primary studies included on bladder cancer in publication
Comparison
Selected as best estimate
Risk estimates
Number of primary studies included
Adjustment level
Heterogeneity
Publication bias (Egger test)
Dietary factors
Yao et al. [19]
Fruit, vegetables
20 CC
11 COH
Fruit and vegetables; high versus low
Yes
RR 0.81; 95 % CI 0.67–0.99
10
Smoking
I2 = 58.4 %
 
   
Fruit; high versus low
Yes
RR 0.77; 95 % CI 0.69–0.87
27
Smoking
I2 = 54.9 %
Egger p = 0.003
   
Vegetables; high versus low
Yes (MMA)
RR 0.81; 95 % CI 0.70–0.93
21
Smoking
I2 = 66.0 %
Egger p = 0.389
   
Citrus Fruits; high versus low
No
RR 0.79; 95 % CI 0.68–0.91
11
 
I2 = 53.2 %
Egger p = 0.034
   
Cruciferous vegetables; high versus low
Yes
RR 0.84; 95 % CI 0.77–0.91
11
 
I2 = 30.7 %
Egger p = 0.443
Steinmaus et al. [21]
Fruit (low intake)
38 CC and COH
Fruits; low versus high
No
RR 1.47; 95 % CI 1.25–1.74
8
Smoking
X2 p = 0.99$
 
 
Vegetables (low intake)
 
Vegetables; low versus high
Yes (MMA)
RR 1.15; 95 % CI 0.98–1.35
8
Smoking
X2 p = 0.82$
 
 
Meat
 
High versus low
No
RR 0.96; 95 % CI 0.73–1.27
4
Smoking
X2 p = 0.97$
 
 
Vitamin A
 
Retinol; low versus high intake
No
RR 1.01; 95 % CI 0.90–1.14
8
 
X2 p = 0.99$
 
 
Carotinoids
 
Carotenoids; low versus high intake
No
RR 1.10; 95 % CI 0.99–1.22
3
 
X2 p = 0.99$
 
Vieira et al. [122]
Fruit, Vegetables
15 COH
Fruit and vegetables; high versus low
No
RR 0.89; 95 % CI 0.75–1.05
8
 
I2 = 33.8 %
 
   
Fruit; high versus low
No
RRs = 0.91; 95 % CI 0.82–1.00
11
Smoking
I2 = 11.0 %
Egger p = 0.48
   
Vegetables; high versus low
No
RRs = 0.92; 95 % CI 0.84–1.01
9
Smoking
I2 = 5.0 %
Egger p = 0.02
   
Citrus fruit; high versus low
No
RRs = 0.88; 95 % CI 0.77–1.01
6
Smoking
I2 = 0.0 %
Egger p = 0.38
   
Cruciferous vegetables; high versus low
No
RRs = 0.85; 95 % CI 0.69–1.06
6
Smoking
I2 = 62.6 %
Egger p = 0.5
Liu et al. [123]
Fruit, vegetables
15 CC
12 COH
Fruit and vegetables; high versus low
No
RR 0.83; 95 % CI 0.69–1.01
9
 
I2 = 57.0 %
 
   
Fruit; high versus low
No
RR 0.81; 95 % CI 0.73–0.89
27
 
I2 = 53.7 %
Egger p = 0.052
   
Vegetables; high versus low
No
RR 0.84; 95 % CI 0.72–0.96
24
 
I2 = 76.3 %
Egger p = 0.74
Xu et al. [124]
Fruit, vegetables
14 COH
Fruit and vegetables; every 0.2 serving increment per day
No
RR 1.00; 95 % CI 0.99–1.00
8
 
I2 = 38.5 %
 
   
Fruit; every 0.2 serving increment per day
No
RRs = 1.00; 95 % CI 0.99–1.00
14
Smoking
I2 = 45.8 %
Egger p < 0.01
   
Vegetables; every 0.2 serving increment per day
No
RRs = 1.00; 95 % CI 0.99–1.00
14
Smoking
I2 = 19.0 %
Egger p = 0.93
   
Citrus fruit; every 0.2 serving increment per day
No
RRs = 1.00; 95 % CI 1.00–1.00
7
 
I2 = 0.0 %
 
   
Cruciferous vegetables; every 0.2 serving increment per day
No
RRs = 0.97; 95 % CI 0.93–1.01
8
 
I2 = 55.8 %
 
Liang et al. [20]
Citrus fruits
8 CC
6 COH
Citrus fruits; high versus low
Yes
RR 0.85; 95 % CI 0.76–0.94
14
 
I2 = 72.1 %
Egger p = 0.004
  
6 COH
Citrus fruits; high versus low
No
RR 0.96; 95 % CI 0.87–1.07
6
 
I2 = 19.8 %
 
  
8 CC
Citrus fruits; high versus low
No
RR 0.77; 95 % CI 0.64–0.92
8
 
I2 = 68.7 %
 
Liu et al. [121]
Cruciferous vegetables
5 CC
5 COH
Cruciferous vegetables; high versus low
No
RR 0.80; 95 % CI 0.69–0.92
10
 
I2 = 45.9 %
Egger p = 0.51
  
5 COH
Cruciferous vegetables; high versus low
No
Cohort: RR 0.86; 95 % CI 0.61–1.11
5
 
I2 = 73 %
 
  
5 CC
Cruciferous vegetables; high versus low
No
CC: RR 0.78; 95 % CI 0.67–0.89
5
 
I2 = 0.0 %
 
Bai et al. [22]
Total fluid intake
17 CC
4 COH
High versus low
Yes
RRm = 1.12; 95 % CI 0.94–1.33
14
Most adjusted
I2 = 82.8 %
Egger p = 0.059
Isa (submitted)
Total fluid intake
15 CC
3 COH
250 ml/day increment
No
RR 1.02; 95 % CI 1.00–1.04
15
  
Egger p = 0.614
Zhang et al. [126]
Tea
7 COH
All tea; high versus low
No
RR 0.92; 95 % CI 0.76–1.13
7
 
I2 = 23.8 %
 
   
All tea; one cup/day increment
No
RR 0.98; 95 % CI 0.93–1.02
7
 
I2 = 44.1 %
 
   
Green tea; one cup/day increment
No
RR 1.02; 95 % CI 0.95–1.11
3
 
I2 = 63.9 %
 
   
Black tea; one cup/day increment
No
RR 0.73; 95 % CI 0.33–1.60
1
   
Wu et al. [127]
Tea
12 CC
3 COH
All tea; high versus low
No
RRm = 1.01; 95 % CI 0.80–1.29
7
Most adjusted
 
Egger p = 0.88
   
Green tea; high versus low
No
RR 1.03; 95 % CI 0.82–1.31
5
 
I2 = 0.0 %
Egger p = 0.49
   
Black tea; high versus low
No
RR 0.84; 95 % CI 0.7–1.01
6
 
I2 = 0.0 %
Egger p = 1.0
Wang et al. [128]
Tea
13 CC
4 COH
All tea; high versus low
No
RRm = 1.12; 95 % CI 0.88–1.43; I2 = 64.6 %; n = 17
17
Most adjusted
 
Egger p = 0.298
   
Green tea; high versus low
No
RR 0.81; 95 % CI 0.68–0.98
4
 
I2 = 0.0 %
Egger p = 0.73
   
Black tea; high versus low
No
RR 1.05; 95 % CI 0.83–1.32
5
 
I2 = 49.4 %
Egger p = 0.41
Qin et al. [130]
Tea
17 CC
6 COH
All tea; high versus low
Yes
RR 0.94; 95 % CI 0.85–1.04
23
 
I2 = 28.3 %
Egger p = 0.52
   
Green tea; high versus low
No
RR 0.97; 95 % CI 0.73–1.21;
5
 
I2 = 0.0 %
Egger p = 0.38
   
Black tea; high versus low
No
RR 0.79; 95 % CI 0.59–0.99
7
 
I2 = 33.1 %
Egger p = 0.38
Huang et al. [24]
Coffee
5 COH
High versus none/low
No
RR 1.08; 95 % CI 0.71–1.66
5
 
I2 = 62.9 %
 
Zhou et al. [25]
Coffee
20 CC
5 COH
High (>5–6 cups/day) versus none
No
Case–control: RRs = 1.45; 95 % CI 1.29–1.63
This category was not calculated for cohort studies
20
 
I2 = 31.8 %
No publication bias (no test estimate reported)
Sala et al. [28]
Coffee
Pooled analysis of 10 CC
6–9 cups versus none
No
RRm = 1.0; 95 % CI 0.6–1.4
 
Most adjusted, analysis restricted to non-smokers
  
   
≥10 cups versus none
No
RRm = 1.8; 95 % CI 1.0–3.3
 
Most adjusted, analysis restricted to non-smokers
  
Villanueva et al. [27]
Coffee
Pooled analysis of 6 CC
>5 cups/day versus ≤5 cups/day; overall
Yes (MMA)
RRms = 1.25; 95 % CI 1.08–1.44
6
Most adjusted, incl. smoking
  
   
>5 cups/day versus ≤5 cups/day; men only
No
RRms = 1.23; 95 % CI 1.05–1.44
5
Most adjusted, incl. smoking
  
   
>5 cups/day versus ≤5 cups/day; women only
No
RRms = 1.31; 95 % CI 0.99–1.74
5
Most adjusted, incl. smoking
  
   
1 l/day increment
No
RRms = 1.24; 95 % CI 1.08–1.43
6
Most adjusted, incl. smoking
  
Yu et al. [26]
Coffee
9 COH
Drinkers versus none/lowest
Yes (MMA)
RR 0.83; 95 % CI 0.73–0.94
9
 
I2 = 39.3 %
Egger p = 0.793
Wu et al. [29]
Coffee
34 CC
6 COH
High versus low
Yes (MMA)
RRms = 1.28; 95 % CI 1.21–1.46
18
Most adjusted, incl. smoking
I2 = 28.5
Egger p = 0.051
Boyle et al. [30]
Sweetened carbonated beverages
5 studies
High versus low
Yes
RR 1.13; 95 % CI 0.89–1.45
5
 
I2 = 0.0 %
Egger p = 0.05
Li et al. [135]
Milk
Dairy products
12 CC
6 COH
Milk; high versus low
Yes
RRm = 0.91; 95 % CI 0.72–1.15
7
Most adjusted
Q p = 0.020
Egger p = 0.048
   
Dairy products; high versus low
Yes
RRm = 1.01; 95 % CI 0.86–1.19
3
Most adjusted
Q p = 0.108
Egger p = 0.73
Mao et al. [31]
Milk and Dairy products
8 HCC
5 PCC
6 COH
All milk; high versus low
No
RRms = 0.84; 95 % CI 0.72–0.97
16
Most adjusted, incl. smoking
I2 = 70.1 %
Egger p = 0.055
   
Whole milk; high versus low
No
RR 2.23; 95 % CI 1.45–3.00
2
 
I2 = 0
 
   
Skim milk; high versus low
No
RR 0.47; 95 % CI 0.18–0.79
2
 
I2 = 0
 
   
Fermented milk; high versus low
No
RR 0.69; 95 % CI 0.47–0.91
5
 
I2 = 62.5 %
 
Li et al. [32]
Fish
6 HCC
3 PCC
5 COH
High versus low
Yes
RRs = 0.86; 95 % CI 0.61–1.12; I2 = 85.4 %; n = 14; Begg’s p = 0.101
14
Smoking
  
Li et al. [33]
Meat
9 CC
5 COH
Red meat; high versus low
Yes
RR 1.15; 95 % CI 0.97–1.36
14
 
I2 = 73.5 %
Egger p = 0.83
  
6 CC
5 COH
Processed meat; high versus low
Yes
RR 1.22; 95 % CI 1.04–1.43
11
 
I2 = 64.9 %
Egger p = 0.35
Pelucchi et al. [34]
Alcohol
14 CC
2 NCC
3 COH
Heavy intake, ≥ 3 drinks (≥ 37.5 g)/day versus non-drinkers
Yes
RR 0.97; 95 % CI 0.72–1.31
7
Smoking
X2 p < 0.01
 
   
Moderate intake, <3 drinks/day versus non-drinkers
No
RR 0.98; 95 % CI 0.89–1.07
15
Smoking
X2 p = 0.05
 
Bagnardi et al. [139]
Alcohol
9 CC
2 COH
Highest category (100 g/day) versus non-drinkers
No
RR 1.17; 95 % CI: 0.97–1.41
11
 
Het. p = N.S.
 
   
Highest category (100 g/day) versus non-drinkers
No
RRs = 1.09; 95 % CI: 0.89–1.33
 
Smoking
Het. p < 0.05
 
Zeegers et al. [140]
Alcohol
6 studies
Current alcohol use versus non-use
No
RR 1.3; 95 % CI 1.1–1.5
6
   
Li et al. [35]
Egg
9 CC
4 COH
All eggs; high versus low
Yes
RRm = 1.11; 95 % CI 0.73–1.69
6
Most adjusted
I2 = 75.8 %
Egger p = 0.55
   
Fried eggs; high versus low
No
RR 2.04; 95 % CI 1.41–2.95
2
 
I2 = 0.0 %
 
   
Boiled eggs; high versus low
No
RR 1.25; 95 % CI 0.82–1.91
2
 
I2 = 35.5 %
 
Pelucchi et al. [45]
Dietary acrylamide
1 CC
1 COH
1 C-COH
High versus low
Yes
RR 0.93; 95 % CI 0.78–1.11
3
 
X2 p = 0.91
 
   
10 mg/day increase in intake
No
RR 1.00; 95 % CI 0.96–1.03
3
 
X2 p = 0.97
 
Tang et al. [36]
Vitamin A (total)
14 CC
11 COH
Supplement, diet and blood levels; high versus low
Yes
RRms = 0.82; 95 % CI 0.65–0.95
11
Most adjusted, incl. smoking
I2 = 46.3 %
Egger p = 0.057
   
Dietary intake; high versus low
No
RRms = 0.90; 95 % CI 0.80–1.01
 
Most adjusted, incl. smoking
I2 = 0 %
 
   
Supplementation versus placebo or no supplementation
Yes
RRms = 0.64; 95 % CI 0.47–0.82
 
Most adjusted, incl. smoking
I2 = 0 %
 
Jeon et al. [37]
Beta-carotene supplements
2 RCT
Supplementation versus placebo or no supplementation
No
RR 1.52; 95 % CI 1.03–2.24
2
 
I2 = 0.0 %
 
Liao et al. [39]
Vitamin D
1 CC
2 NCC
2 COH
Serum levels; high versus low
Yes
RRs = 0.75; 95 % CI 0.65–0.87
5
Smoking
I2 = 0.0 %
Egger p = 0.57
Chen et al. [40]
Vitamin D
1 CC
3 COH
Circulating levels; high versus low
No
RR 0.75; 95 % CI 0.57–0.99
4
 
I2 = 51.7 %
Egger p = 0.87
  
3 studies
Diet and supplement; high versus low
No
RR 0.92; 95 % CI 0.66–1.28
3
 
I2 = 32.3 %
Egger p = 0.41
 
Vitamin E
4 CC
5 COH
Diet; high versus low
No
RRm = 0.69; 95 % CI 0.52–0.92
5
 
I2 = 47.1 %
Egger p = 0.01
  
3 CC
3 COH
Diet and supplement; high versus low
No
RRm = 0.76; 95 % CI 0.56–1.02
5
 
I2 = 49.8 %
Egger p = 0.35
  
1 CC
6 COH
Supplementation versus placebo or no supplementation
No
RRm = 0.64; 95 % CI 0.48–0.85
  
I2 = 0.6 %
Egger p = 0.39
 
Vitamin C
7 CC
7 COH
Diet; High versus Low
No
RRm = 0.69; 95 % CI 0.58–0.82
6
 
I2 = 13.7 %
Egger p = 0.28
  
5 CC
3 COH
Diet and supplement; high versus low
No
RRm = 0.80; 95 % CI 0.62–1.03
5
 
I2 = 33.4 %
Egger p = 0.03
  
6 CC
3 COH
Supplementation versus placebo or no supplementation
No
RRm = 0.84; 95 % CI 0.55–1.29
4
 
I2 = 74.4 %
Egger p = 0.002
Wang et al. [38]
Vitamin C
11 CC
9 COH
Intake; high versus low
Yes
RRs = 0.90; 95 % CI 0.79–1.00
20
Smoking
I2 = 43.7 %
Egger p = 0.064
 
Vitamin E
7 CC
8 COH
Intake; high versus low
Yes
RRs = 0.82; 95 % CI 0.74–0.90
15
Smoking
I2 = 0 %
Egger p = 0.534
He et al. [41]
Folate
6 CC
7 COH
Intake; high versus low
Yes
RR 0.84; 95 % CI 0.72–0.96
13
 
I2 = 28.9 %
Egger p = 0.06
Myung et al. [37]
Antioxidant supplement
4 RCT
Supplementation versus placebo or no supplementation
No
RR 1.52; 95 % CI 1.06–2.17
4
 
I2 = 0.0 %
 
Amaral et al. [42]
Selenium
3 CC
3 NCC
1 C-COH
Serum and toenail levels; high versus low
Yes
OR = 0.61; 95 % CI 0.42–0.87
7
 
I2 = 60.8 %
Egger p = 0.357
Vinceti et al. [43] (Cochrane SR)
Selenium
5 prospective studies
Serum, toenail or plasma levels; high versus low
No
OR = 0.67; 95 % CI 0.46–0.97
5
 
I2 = 30 %
 
  
2 RCT
Supplementation versus Placebo
Yes
RR 1.14; 95 % CI 0.81–1.61
2
 
I2 = 0.0 %
 
Sun et al. [46]
Obesity
15 COH
Obese versus normal weight
Yes
RRs = 1.10; 95 % CI 1.03–1.18
12
Smoking
I2 = 8.8 %
Egger p = 0.712
   
Pre-obese versus normal weight
Yes
RRs = 1.07; 95 % CI 0.99–1.16
13
Smoking
I2 = 46.1 %
Egger p = 0.712
Qin et al. [47]
Obesity
11 COH
Obese versus normal weight
No
RRs = 1.09; 95 % CI 1.01–1.17
9
Smoking
I2 = 35.9 %
Egger p = 0.244
Behavioural factors
Hemelt et al. [11]
Smoking
21 CC
11 COH
2 NCC
All tobacco; Ever smokers versus never smokers
No
RR 2.25; 95 % CI 1.96–2.59
15
   
   
All tobacco; Ex smokers versus never smokers
No
RR 1.90; 95 % CI 1.71–2.11
8
   
   
All tobacco; Current smokers versus never smokers
No
RR 3.35; 95 % CI 2.90–3.88
11
   
   
Cigarettes; Ever smokers versus never smokers
No
RR 2.24; 95 % CI 1.81–2.78
9
   
   
Cigarettes; Ex smokers versus never smokers
No
RR 1.95; 95 % CI 1.55–2.47
4
   
   
Cigarettes; Current smokers versus never smokers
No
RR 3.13; 95 % CI 2.33–4.21
6
   
Puente et al. [48]
Smoking
Pooled analysis of 14 CC
Current smokers versus never smokers; Male
No
RR 3.89; 95 % CI 3.53–4.29
    
   
Current smokers versus never smokers; Female
No
RR 3.55; 95 % CI 3.06–4.10
    
   
Ex-smokers versus never smokers; Male
No
RR 2.21; 95 % CI 2.01–2.43
    
   
Ex-smokers versus never smokers; Female
No
RR 2.21; 95 % CI 1.87–2.61
    
Freedman et al. [49]
Smoking
7 COH
Current smokers versus never smokers
No
RR 2.94; 95 % CI 2.45–3.54
7
 
I2 = 0.0 %
Egger p = 0.32
Brennan et al. [50]
Smoking
Pooled analysis of 11 CC (men only)
Ever-smokers versus never smokers
No
RR 3.63; 95 % CI 3.13–4.20
    
   
Current smokers versus never and ex-smokers
No
RR 2.47; 95 % CI 2.23–2.74
    
Brennan et al. [51]
Smoking
Pooled analysis of 11 CC (women only)
Ever-smokers versus never smokers
No
RR 3.1; 95 % CI 2.5–3.9
    
   
Current smokers versus never and ex-smokers
No
RR 2.9; 95 % CI 2.3–3.7
    
Van Osch et al. submitted [10]
Active smoking
18 COH
71 CC
Active smoking; Ex-smokers versus never smokers
Yes
RR 1.83; 95 % CI 1.52–2.14
12
Age, sex
 
Egger p = 0.150
   
Active smoking; Current smokers versus never smokers
Yes
RR 3.14; 95 % CI 2.53–3.75
13
Age, sex
  
   
Active smoking; ≤20 versus >20 years at first exposure
No
RR 1.33; 95 % CI 0.92–1.74
4
   
Cumberbatch et al. [53]
Active smoking
 
Ex-smokers versus never smokers
No
RR 3.37; 95 % CI 3.01–3.78
48
Most adjusted estimates in MA
I2 = 82.2 %
Egger p = 0.13
Begg p = 0.03
   
Current smokers versus never smokers
No
RR 1.98; 95 % CI 1.76–2.22
49
Most adjusted estimates in MA
I2 = 78.6 %
 
   
Pipe; Smokers versus never smokers
No
RR 1.49; 95 % CI 1.18–1.88
4
 
I2 = 39.4 %
 
   
Cigar; Smokers versus never smokers
No
RR 1.62; 95 % CI 1.18–2.22
4
 
I2 = 0.0 %
 
 
Smokeless tobacco
 
Snuff; users versus non-users
No
RR 0.89; 95 % CI 0.56–1.42
2
 
I2 = 23.7 %
 
   
Chewing tobacco; users versus non-users
No
RR 1.04; 95 % CI 0.75–1.45
2
 
I2 = 0.0 %
 
Pitard et al. [52]
Active smoking
Pooled analysis of 6 CC (men only)
Pipe only; Smokers versus never smokers
Yes
RR 1.9; 95 % CI 1.2–3.1
    
   
Cigar only; Smokers versus never smokers
Yes
RR 2.3; 95 % CI 1.6–3.5
    
   
Cigarette only; Smokers versus never smokers
No
RR 3.5; 95 % CI 2.9–4.2
    
Van Hemelrijck et al. [54]
Passive smoking
5 CC
3 COH
Exposed versus not exposed
Yes
RR 0.99; 95 % CI 0.86–1.14
8
Non-smokers only
I2 = 35.6 %
Begg p = 0.32
Lee et al. [55]
Smokeless tobacco
12 CC
1 COH
Smokeless tobacco use versus never use
Yes
RRs = 0.95; 95 % CI 0.71–1.29
9
Smoking
I2 = 59.6 %
 
Keimling et al. [56]
Physical activity
4 CC
11 COH
High versus low
Yes
RRm = 0.86; 95 % CI 0.77–0.95
7
Most adjusted
I2 = 0.0 %
 
Turati et al. [57]
Personal hair dye
15 CC
2 COH
Personal use of any type of hair dyes versus no use
Yes
RRs = 0.94; 95 % CI 0.82–1.08
12
Smoking
I2 = 49.9 %
Egger p = 0.54
Occupational (Comparing the specific occupation versus any other occupation or the general population)
         
Guha et al. [158]
Painters
30 CC
2 COH
9 RL
Painters
No
RR 1.25; 95 % CI 1.16–1.34
41
 
I2 = 23.5 %
 
   
Painters
No
RRs = 1.28; 95 % CI 1.15–1.43
 
Smoking
I2 = 0.7 %
 
   
Painters
No
RRms = 1.27; 95 % CI 0.99–1.63
 
Most adjusted, incl. smoking
I2 = 0.1 %
 
Bachand et al. [159]
Painters
33 CC
Painters
No
RR 1.30; 95 % CI 1.17–1.44
33
Smoking; morbidity and mortality combined
  
  
4 COH
Painters
No
RR 1.23; 95 % CI 0.95–1.59
4
Smoking; morbidity only
  
Harling et al. [161]
Hairdressers
28 CC
14 RCOH
Hairdressers
No
RR 1.35; 95 % CI 1.13–1.61
23
Smoking
X2 p = 0.19
 
   
Hairdressers; job held ≥ 10 years
No
RR 1.70; 95 % CI 1.01–2.88
6
 
X2 p = 0.46
 
Takkouche et al. [160]
Hairdressers
26 CC
8 COH
Hairdressers
No
RR 1.33; 95 % CI 1.07–1.67
19
Smoking
Q p = 0.77
 
   
Hairdressers
No
RR 1.35; 95 % CI 1.21–1.50
26
Incidence only
Q p = 0.78
 
‘t Mannetje et al. [162]
Sales workers
10 CC
2 RL
3 mortality studies
Sales workers; Men
No
RR 1.04; 95 % CI 0.97–1.12
 
Smoking, incidence only
Q p = 0.3
Egger p = 0.4
   
Sales workers; Women
No
RR 1.22; 95 % CI 1.06–1.41
 
Smoking, incidence only
Q p = 0.44
Egger p < 0.01
Manju L et al. [164]
Motor vehicle driving
3 COH
Overall (motor vehicle drivers and railroad workers)
No
RR 1.08; 95 % CI 1.00–1.17
3
 
Het. p = 0.85
 
  
27 CC
Truck drivers
No
RR 1.18; 95 % CI 1.09–1.28
18
 
Het. p = 0.25
 
  
27 CC
Bus drivers
No
RR 1.23; 95 % CI 1.06–1.44
11
 
Het. p = 0.19
 
Boffetta and Silverman [163]
Motor vehicle driving
16 CC
7 COH
6 routinely collected data
(men only)
Truck drivers
No
RR 1.17; 95 % CI 1.06–1.29
15
 
Het. p = 0.3
Egger p = 0.07
   
Bus drivers
No
RR 1.33; 95 % CI 1.22–1.45
10
 
Het. p = 0.4
Egger p = 0.001
Acquavella et al. [165]
Farmers
10 Follow-up studies
8 CC
11 PMR
(men only)
Farmers
No
RR 0.79; 95 % CI 0.72–0.86
29
 
X2 p < 1*10−5
 
  
10 Follow-up studies
Farmers
No
RR 0.62; 95 % CI 0.59–0.65
10
 
X2 p = 0.08
 
  
8 CC
Farmers
No
RR 0.94; 95 % CI 0.86–1.04
8
 
X2 p = 0.09
 
Gaertner et al. [166]
Foundry workers
22 CC
9 COH
14 surveillance studies
Foundry workers
No
RR 1.11; 95 % CI 0.96–1.29
16 (CC only)
Smoking
X2 p = 0.07 (15df)
 
   
Foundry workers
No
RR 1.14; 95 % CI 1.04–1.26;
11
Incidence only
X2 p = 0.28 (10df)
 
Mastrangelo et al. [167]
Textile workers
Unknown
Spinners
No
RR 1.19; 95 % CI 0.80–1.57
2
 
X2 p < 0.001$
 
   
Weavers
No
RR 2.40; 95 % CI 1.62–3.18
2
 
X2 p = 0.001$
 
   
Dyers
No
RR 1.39; 95 % CI 1.07–1.71
3
 
X2 p = 0.505$
 
Tokumaru et al. [168]
Flight attendants
3 COH (female only)
Flight attendants
No
RR 2.03; 95 % CI 0.75–5.43
3
Incidence only
Q p = N.S.
 
Buja et al. [169]
Flight attendants
4 COH (female only)
Flight attendants
No
RR 1.45; 95 % CI 0.33–3.16
4
Incidence only
Tau = 0.39
 
Baena et al. [171]
Petroleum industry
8 CC
Petroleum industry workers
No
RR 1.5; 95 % CI 1.29–1.75
8
   
Greenberg et al. [172]
Chemical workers
19 COH for incidence
Chemical workers
No
RR 2.21; 95 % CI 1.18–4.15
19
Incidence only
  
Vlaanderen et al. [173]
Dry cleaning
4 CC
3 COH
Dry cleaning workers
No
RR 1.47; 95 % CI 1.16–1.85
7
 
I2 = 0 %
Egger p > 0.05
Fu et al. [174]
Inorganic lead compounds
5 studies
Exposed to inorganic lead compounds versus non-exposed
No
RR 1.41; 95 % CI 1.16–1.71
5
 
Hom. p > 0.30
 
Collins et al. [176]
Acrylonitrile workers
10 studies
Acrylonitrile workers
No
RR 0.8; 95 % CI 0.3–2.2
3
Incidence
Het. p = 0.49
 
Rota et al. [179]
Polycyclic aromatic hydrocarbons (PAHs)
13 COH
Aluminium production workers
No
RR 1.28; 95 % CI 0.98–1.68
10
 
X2 p = 0.002
Egger p = 0.22
   
Asphalt workers
No
RR 1.03; 95 % CI 0.82–1.30
2
 
X2 p = 0.31
 
   
Carbon black production
No
RR 1.10; 95 % CI 0.61–2.00
3
 
X2 p = 0.29
Egger p = 0.61
   
Workers in iron and steel foundry
No
RR 1.38; 95 % CI 1.00–1.91
9
 
X2 p = 0.001
Egger p = 0.3
95 % CI 95 % confidence interval, CC case–control study, C-COH case-cohort study, COH cohort study, df degrees of freedom, ECO ecological study, HCC hospital-based case–Control study, Het. heterogeneity, Hom. homogeneity, NCC nested case–control study, N.S. not significant, OR odds ratio, PCC population-based case–control study, PCOH prospective cohort study, PMR proportional mortality ratio, RCOH retrospective cohort study, RE risk estimate, RCT randomised controlled trial, RL record linkage study, RR relative risk, SIR standardised incidence ratio
$The p value was calculated by the authors of the current article when only the X 2 statistic and degrees of freedom were presented

Appendix 3

See Table 4.
Table 4
Risk estimates for occupations reported by Cumberbatch et al., Reulen et al., Kogevinas et al., and ‘t Mannetje et al
Cumberbatch et al. [53] (Meta-analysis of 217 studies)
Reulen et al. [62]
(Meta-analysis of 66 cohort studies and 64 case–control studies)
Kogevinas et al. [63]
(Pooled analysis of 11 European CC studies)
‘t Mannetje et al. [64]
(Pooled analysis of 11 European CC studies)
Occupation
RRs (95 % CI)
Occupation
RRs (95 % CI)
Occupations (ISCO code*)[183]
RR (95 % CI)
Occupations (ISCO codes)
RR (95 % CI)
Occupations with statistically significant results
Tobacco workers
1.72 (1.37–2.15)
Blacksmiths
1.58 (1.05–2.36)
Working proprietors—wholesale and retail trade (41)
1.33 (1.04–1.69)
Blacksmiths, toolmakers and machine-tool operators (83)
1.9 (1.1–3.6)
Dye workers
1.58 (1.32–1.90)
Blacksmiths and tool-makers
1.22 (1.09–1.35)
Working proprietor—retail trade (41030)
1.35 (1.02–1.79)
Lathe operator (83420)
4.6 (1.1–19.2)
Chimney sweeps
1.53 (1.30–1.81)
Building finishers
1.16 (1.02–1.33)
Working proprietor—cafe. bar and snack bar (51050)
2.2 (1.16–4.20)
Blacksmiths, toolmakers and machine-tool operators nec. (839)
2.9 (1.3–6.3)
Nurses
1.49 (1.06–2.08)
Domestic helpers
1.39 (1.14–1.70)
Concierge—apartment house (55120)
2.64 (1.10–6.32)
Field crop and vegetable farm workers (622)
1.8 (1.0–3.1)
Rubber workers
1.49 (1.37–1.61)
Dye makers
1.14 (1.09–1.19)
Janitor (55130)
2.28 (1.30–3.98)
Tobacco prepares and tobacco product makers (78)
3.1 (1.1–9.3)
Waiters
1.43 (1.34–1.52)
Furnace operators
1.41 (1.11–1.79)
Nursery workers and gardeners (627)
1.5 (1.07–2.10)
Tailors and dressmakers (791)
1.4 (1.0–2.1)
Aluminum workers
1.41 (1.29–1.55)
Glass-makers
1.69 (1.13–2.52)
Other nursery workers and gardeners (62790)
3.57 (1.24–10.29)
Other saleswomen, shop assistants and demonstrators (45190)
2.6 (1.0–6.9)
Hairdressers
1.32 (1.24–1.40)
Launderers
1.72 (1.25–2.37)
Supervisor and general foreman—metal processing—(70030)
2.11 (1.04–4.32)
Mail sorting clerk (37020)
4.4 (1.0–19.5)
Printers
1.23 (1.17–1.30)
Leather workers
1.37 (1.10–1.70)
Supervisor and general foreman—manufacturing of machinery and metal products (70050)
1.59 (1.05–2.42)
  
Seamen
1.23 (1.17–1.29)
Machine-tool setters
1.31 (1.12–1.53)
Miners, quarrymen, well drillers and related workers (71)
1.26 (1.00–1.58)
  
Oil and petroleum workers
1.2 (1.06–1.37)
Machinist
1.16 (1.04–1.29)
Miners and quarrymen (711)
1.3 (1.02–1.64)
  
Shoe and leather workers
1.2 (1.12–1.29)
Mechanics
1.20 (1.06–1.35)
Metal casters (724)
1.96 (1.06–3.64)
  
Plumbers
1.2 (1.14–1.27)
Metal processors
1.24 (1.11–1.38)
Metal processers NEC (729)
1.85 (1.15–2.97)
  
Sales agents
1.17 (1.15–1.20)
Metal workers
1.15 (1.01–1.32)
Knitters (755)
2.56 (1.24–5.30)
  
Artistic workers
1.16 (1.10–1.22)
Miners
1.57 (1.21–2.03)
Knitting-machine operator-hosiery (75530)
3.26 (1.26–8.40)
  
Cooks and stewards
1.15 (1.08–1.22)
Motor mechanics
1.39 (1.11–1.73)
Metal workers and machinists (832–835, 841, 849)
1.16 (1.02–1.32)
  
Chemical process workers
1.14 (1.10–1.19)
Paper-pulp workers
1.29 (1.02–1.63)
Machine-tool setter-operators (833)
1.5 (1.07–2.12)
  
Metal workers
1.14 (1.11–1.18)
Rubber workers
1.43 (1.18–1.71)
Metalworking machine setter—general (83305)
2.27 (1.03–5.00)
  
Drivers
1.14 (1.11–1.16)
Writers and artists
1.34 (1.06–1.71)
Metalworking machine setter-operator—general—(83310)
3.35 (1.19–9.44)
  
Fishermen
1.13 (1.08–1.19)
  
Precision-grinding-machine setter-operator—(83370)
5.21 (1.48–18.31)
  
Painters
1.13 (1.09–1.17)
  
Machinery fitters, machine assemblers and precision-instrument makers—except electrical (84)
1.16 (1.01–1.34)
  
Assistant nurses
1.12 (1.04–1.20)
  
Automobile mechanic (84320)
1.38 (1.02–1.87)
  
Domestic assistants
1.12 (1.07–1.18)
  
Machinery fitters, machine assemblers and precision-instrument makers—except electrical—NEC (849)
1.27 (1.03–1.55)
  
Launderers and dry cleaners
1.12 (1.04–1.21)
  
Textile machinery mechanic (84945)
2.86 (1.50–5.47)
  
Public safety workers–police
1.11 (1.07–1.16)
  
Other electrical fitters (85190)
3.99 (1.10–14.51)
  
Physicians
1.11 (1.03–1.19)
  
Electric arc welder—hand (87220)
2.27 (1.04–4.98)
  
Clerical workers
1.11 (1.10–1.13)
  
Printers and related workers (92)
1.45 (1.07–1.97)
  
Electrical workers
1.11 (1.07–1.14)
  
Printing pressmen (922)
1.81 (1.03–3.17)
  
Military personnel
1.11 (1.05–1.18)
  
Automobile painter (93960)
1.95 (1.01–3.75)
  
Mechanics
1.11 (1.09–1.13)
  
Excavating-machine operator (97420)
2.43 (1.18–5.00)
  
Smelting workers
1.11 (1.06–1.16)
  
Transport equipment operators (98)
1.17 (1.02–1.34)
  
Transport workers
1.1 (1.06–1.13)
      
Glass makers, etc.
1.1 (1.05–1.15)
      
Textile workers
1.1 (1.06–1.14)
      
Waiters and bartenders
1.1 (1.01–1.19)
      
Building caretakers
1.09 (1.06–1.13)
      
Health care workers
1.09 (1.06–1.12)
      
Food manufacturing workers
1.08 (1.04–1.12)
      
Postal workers
1.08 (1.03–1.13)
      
Packers, loaders, and warehouse workers
1.08 (1.04–1.13)
      
Shop workers
1.07 (1.05–1.10)
      
Technical workers, etc.
1.04 (1.02–1.06)
      
Economically inactive
0.96 (0.95–0.97)
      
Religious and legal workers, etc.
0.93 (0.88–0.97)
      
Forestry workers
0.88 (0.86–0.90)
      
Teachers
0.85 (0.82–0.87)
      
Gardeners
0.78 (0.75–0.81)
      
Farmers
0.69 (0.68–0.71)
      
Occupations with no statistically significant results
Beverage workers
1.35 (0.84–2.16)
Architects and engineers
0.99 (0.85–1.16)
Medical doctors (061)
0.82 (0.40–1.69)
Hairdressers, barbers, beauticians and related workers (57)
0.8 (0.4–1.7)
Iron and metal ware workers
1.18 (0.98–1.42)
Armed forces
1.09 (0.90–1.33)
Nurses (071–079)
0.89 (0.51–1.56)
Chemical processors and related workers (74)
0.6 (0.2–2.2)
Other health workers
1.11 (0.97–1.27)
Bakers
1.02 (0.54–1.92)
Teachers (13)
1 (0.74–1.34)
Spinners, weavers, knitters, dyers and related workers (75)
0.9 (0.6–1.3)
Dentists
1.09 (0.96–1.23)
Bricklayers
1.15 (0.96–1.38)
Salesmen, shop assistants (45)
0.97 (0.82–1.14)
Shoe makers and leather goods makers (80)
0.4 (0.2–1.1)
Welders
1.06 (1.00–1.12)
Building caretakers
1.26 (0.88–1.80)
Cooks, waiters, bartenders (53)
1..19 (0.91–1.55)
Metal working including toolmakers, machine-tool setter-operators, metal grinders and machinery fitters (832–835, 841, 849)
1.5 (0.8–2.7)
Bricklayers
1.05 (0.99–1.12)
Building frame workers
1.08 (0.93–1.26)
Launderers, dry-cleaners and pressers (56)
1.24 (0.67–2.31)
Rubber and plastics product makers (90)
1.2 (0.5–3.0)
Miners and quarry workers
1.05 (1.00–1.11)
Butchers
1.38 (0.88–2.18)
Hairdressers (57)
1.09 (0.70–1.70)
  
Laboratory assistants
1.04 (0.92–1.18)
Cabinet makers
0.98 (0.58–1.67)
Fire-fighters (581)
0.66 (0.27–1.62)
  
Mixed occupations
1.02 (1.00–1.04)
Carpenters
1.04 (0.80–1.35)
Farmers (61)
0.94 (0.77–1.14)
  
Public safety workers–firefighters
1.00 (0.90–1.12)
Cleaners
1.25 (0.86–1.80)
Production supervisors and general foremen (70)
1.1 (0.89–1.37)
  
Other construction workers
0.98 (0.96–1.00)
Clerks
0.92 (0.83–1.02)
Metal processers (72)
1.14 (0.93–1.39)
  
Engine and motor operators
0.91 (0.55–1.51)
Cooks
1.13 (0.93–1.38)
Sawyers, plywood makers and related wood-processing workers (732)
1.51 (0.91–2.48)
  
Other workers
0.48 (0.13–1.80)
Electricians
1.04 (0.87–1.24)
Chemical processors (74)
1.09 (0.82–1.45)
  
  
Firefighters
1.26 (0.76–2.09)
Petroleum-refining workers (745)
0.52 (0.10–2.69)
  
  
Fishery workers
0.81 (0.62–1.06)
Textile workers (75)
1.05 (0.81–1.36)
  
  
Food processors
1.03 (0.90–1.18)
Butchers and meat preparers (773)
0.99 (0.70–1.41)
  
  
Forestry workers
1.00 (0.80–1.24)
Food preservers (774)
1.07 (0.34–3.32)
  
  
Freight handlers
1.10 (0.94–1.28)
Dairy product processers (775)
1.26 (0.61–2.60)
  
  
Gardeners
1.19 (0.84–1.70)
Tailors, dressmakers, sewers, upholsterers (79)
1.07 (0.77–1.49)
  
  
Hand packers
0.99 (0.70–1.41)
Leather workers (801–803)
1.31 (0.89–1.94)
  
  
Health professionals
1.07 (0.87–1.31)
Motor-vehicle mechanics (843)
1.16 (0.90–1.50)
  
  
Managers
1.39 (0.95–2.03)
Electrical fitters and related electrical and electronics workers (85)
1.1 (0.91–1.34)
  
  
Nurses
0.90 (0.44–1.85)
Plumbers (871)
0.98 (0.69–1.39)
  
  
Plumbers
1.23 (0.97–1.56)
Welders (872)
1.22 (0.91–1.63)
  
  
Police officers and guards
1.03 (0.78–1.36)
Rubber workers (901, 902)
1.18 (0.84–1.67)
  
  
Printers
1.10 (0.87–1.40)
Paper and paperboard product makers (91)
0.96 (0.41–2.24)
  
  
Protective service occupations
0.94 (0.84–1.05)
Painters (93)
1.17 (0.91–1.50)
  
  
Sheet metal workers
1.09 (0.57–2.07)
Asbestos cement product maker (94330)
0.64 (0.16–2.49)
  
  
Tailors
1.33 (0.93–1.90)
Reinforced concreters, cement finishers and terrazzo workers (952)
1.17 (0.86–1.59)
  
  
Teaching professionals
0.98 (0.70–1.37)
Roofers (953)
0.72 (0.36–1.43)
  
  
Tool-makers
1.17 (0.86–1.59)
Carpenters, joiners and parquetry workers (954)
1.04 (0.81–1.34)
  
  
Welders
1.04 (0.88–1.23)
Plasterers (955)
1.69 (0.84–3.41)
  
    
Insulators (956)
1.67 (0.61–4.59)
  
    
Construction workers NEC (959)
0.88 (0.68–1.16)
  
    
Stationary engine and related equipment operators (96)
1.07 (0.72–1.57)
  
    
Railway engine-drivers and firemen (983)
1.41 (0.87–2.28)
  
    
Railway brakemen, signalmen and shunters (984)
1.43 (0.77–2.63)
  
    
Motor vehicle drivers (985)
1.14 (0.97–1.33)
  
    
Industries (ISIC code$) [184]
   
    
Salt mining (2903)
4.41 (1.43–13.6)
  
    
Manufacture of carpets and rugs (3214)
4.07 (1.44–11.5)
  
    
Manufacture of paints, varnishes and lacquers (3521)
2.94 (1.48–5.84)
  
    
Manufacture of plastic products NEC (356)
1.79 (1.06–3.00)
  
    
Manufacture of industrial chemicals (351)
1.58 (1.07–2.33)
  
    
Education services (931)
1.47 (1.06–2.05)
  
* ISCO (International Standard Classification of Occupations); $ ISIC (International Standard Industrial Classification)
Literatur
1.
Zurück zum Zitat Cancer IA for R on. GLOBOCAN 2012: estimated cancer incidence, mortality and prevalence worldwide in 2012. World Heal. Organ. http//globocan. iarc. fr/Pages/fact_sheets_cancer. aspx. Accessed Sept 2014. Cancer IA for R on. GLOBOCAN 2012: estimated cancer incidence, mortality and prevalence worldwide in 2012. World Heal. Organ. http//globocan. iarc. fr/Pages/fact_sheets_cancer. aspx. Accessed Sept 2014.
2.
Zurück zum Zitat Czene K, Lichtenstein P, Hemminki K. Environmental and heritable causes of cancer among 9.6 million individuals in the Swedish family-cancer database. Int J Cancer. 2002;99:260–6.PubMedCrossRef Czene K, Lichtenstein P, Hemminki K. Environmental and heritable causes of cancer among 9.6 million individuals in the Swedish family-cancer database. Int J Cancer. 2002;99:260–6.PubMedCrossRef
3.
Zurück zum Zitat Burger M, Catto JWF, Dalbagni G, Grossman HB, Herr H, Karakiewicz P, et al. Epidemiology and risk factors of urothelial bladder cancer. Eur Urol. 2013;63:234–41.PubMedCrossRef Burger M, Catto JWF, Dalbagni G, Grossman HB, Herr H, Karakiewicz P, et al. Epidemiology and risk factors of urothelial bladder cancer. Eur Urol. 2013;63:234–41.PubMedCrossRef
4.
Zurück zum Zitat Chavan S, Bray F, Lortet-Tieulent J, Goodman M, Jemal A. International variations in bladder cancer incidence and mortality. Eur Urol. 2014;66:59–73.PubMedCrossRef Chavan S, Bray F, Lortet-Tieulent J, Goodman M, Jemal A. International variations in bladder cancer incidence and mortality. Eur Urol. 2014;66:59–73.PubMedCrossRef
5.
Zurück zum Zitat Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90.PubMedCrossRef Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90.PubMedCrossRef
6.
Zurück zum Zitat Zeegers MPA, Kellen E, Buntinx F, van den Brandt PA. The association between smoking, beverage consumption, diet and bladder cancer: a systematic literature review. World J Urol. 2004;21:392–401.PubMedCrossRef Zeegers MPA, Kellen E, Buntinx F, van den Brandt PA. The association between smoking, beverage consumption, diet and bladder cancer: a systematic literature review. World J Urol. 2004;21:392–401.PubMedCrossRef
7.
9.
Zurück zum Zitat Ng M, Freeman MK, Fleming TD, Robinson M, Dwyer-Lindgren L, Thomson B, et al. Smoking prevalence and cigarette consumption in 187 countries, 1980–2012. JAMA. 2014;311:183–92.PubMedCrossRef Ng M, Freeman MK, Fleming TD, Robinson M, Dwyer-Lindgren L, Thomson B, et al. Smoking prevalence and cigarette consumption in 187 countries, 1980–2012. JAMA. 2014;311:183–92.PubMedCrossRef
10.
Zurück zum Zitat van Osch FHM, Jochems SHJ, van Schooten F-J, Bryan RT, Zeegers MPA. Quantified relations between exposure to tobacco smoking and bladder cancer risk: a meta-analysis of 89 studies. Manuscript submitted for publication. Int J Epidemiol. 2016. doi:10.1093/ije/dyw044. van Osch FHM, Jochems SHJ, van Schooten F-J, Bryan RT, Zeegers MPA. Quantified relations between exposure to tobacco smoking and bladder cancer risk: a meta-analysis of 89 studies. Manuscript submitted for publication. Int J Epidemiol. 2016. doi:10.​1093/​ije/​dyw044.
11.
Zurück zum Zitat Hemelt M, Yamamoto H, Cheng KK, Zeegers MPA. The effect of smoking on the male excess of bladder cancer: a meta-analysis and geographical analyses. Int J Cancer. 2009;124:412–9.PubMedCrossRef Hemelt M, Yamamoto H, Cheng KK, Zeegers MPA. The effect of smoking on the male excess of bladder cancer: a meta-analysis and geographical analyses. Int J Cancer. 2009;124:412–9.PubMedCrossRef
12.
Zurück zum Zitat Clark PE, Agarwal N, Biagioli MC, Eisenberger MA, Greenberg RE, Herr HW, et al. Bladder cancer. J Natl Compr Cancer Netw. 2013;11:446–75. Clark PE, Agarwal N, Biagioli MC, Eisenberger MA, Greenberg RE, Herr HW, et al. Bladder cancer. J Natl Compr Cancer Netw. 2013;11:446–75.
13.
Zurück zum Zitat Yeung C, Dinh T, Lee J. The health economics of bladder cancer: an updated review of the published literature. Pharmacoeconomics. 2014;32:1093–104.PubMedCrossRef Yeung C, Dinh T, Lee J. The health economics of bladder cancer: an updated review of the published literature. Pharmacoeconomics. 2014;32:1093–104.PubMedCrossRef
15.
Zurück zum Zitat Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.PubMedPubMedCentralCrossRef Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.PubMedPubMedCentralCrossRef
16.
Zurück zum Zitat Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Front matter. Introduction to meta-analysis. Chichester: Wiley; 2009.CrossRef Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Front matter. Introduction to meta-analysis. Chichester: Wiley; 2009.CrossRef
18.
Zurück zum Zitat Bouter LM, van Dongen MCJM, Zielhuis GA, Zeegers MP. Leerboek epidemiologie. Houten: Bohn Stafleu van Loghum; 2015. Bouter LM, van Dongen MCJM, Zielhuis GA, Zeegers MP. Leerboek epidemiologie. Houten: Bohn Stafleu van Loghum; 2015.
19.
Zurück zum Zitat Yao B, Yan Y, Ye X, Fang H, Xu H, Liu Y, et al. Intake of fruit and vegetables and risk of bladder cancer: a dose–response meta-analysis of observational studies. Cancer Causes Control. 2014;25:1645–58.PubMedCrossRef Yao B, Yan Y, Ye X, Fang H, Xu H, Liu Y, et al. Intake of fruit and vegetables and risk of bladder cancer: a dose–response meta-analysis of observational studies. Cancer Causes Control. 2014;25:1645–58.PubMedCrossRef
20.
Zurück zum Zitat Liang S, Lv G, Chen W, Jiang J, Wang J. Citrus fruit intake and bladder cancer risk: a meta-analysis of observational studies. Int J Food Sci Nutr. 2014;7486:1–6. Liang S, Lv G, Chen W, Jiang J, Wang J. Citrus fruit intake and bladder cancer risk: a meta-analysis of observational studies. Int J Food Sci Nutr. 2014;7486:1–6.
21.
Zurück zum Zitat Steinmaus CM, Nuñez S, Smith AH. Diet and bladder cancer: a meta-analysis of six dietary variables. Am J Epidemiol. 2000;151:693–702.PubMedCrossRef Steinmaus CM, Nuñez S, Smith AH. Diet and bladder cancer: a meta-analysis of six dietary variables. Am J Epidemiol. 2000;151:693–702.PubMedCrossRef
22.
Zurück zum Zitat Bai Y, Yuan H, Li J, Tang Y, Pu C, Han P. Relationship between bladder cancer and total fluid intake: a meta-analysis of epidemiological evidence. World J Surg Oncol Engl. 2014;12:223.CrossRef Bai Y, Yuan H, Li J, Tang Y, Pu C, Han P. Relationship between bladder cancer and total fluid intake: a meta-analysis of epidemiological evidence. World J Surg Oncol Engl. 2014;12:223.CrossRef
23.
Zurück zum Zitat Qin J, Xie B, Mao Q, Kong D, Lin Y, Zheng X. Tea consumption and risk of bladder cancer: a meta-analysis. World J Surg Oncol Engl. 2012;10:172.CrossRef Qin J, Xie B, Mao Q, Kong D, Lin Y, Zheng X. Tea consumption and risk of bladder cancer: a meta-analysis. World J Surg Oncol Engl. 2012;10:172.CrossRef
24.
Zurück zum Zitat Huang T, Guo Z, Zhang X, Zhang X, Liu H, Geng J, et al. Coffee consumption and urologic cancer risk: a meta-analysis of cohort studies. Int Urol Nephrol. 2014;46:1481–93.PubMedCrossRef Huang T, Guo Z, Zhang X, Zhang X, Liu H, Geng J, et al. Coffee consumption and urologic cancer risk: a meta-analysis of cohort studies. Int Urol Nephrol. 2014;46:1481–93.PubMedCrossRef
25.
Zurück zum Zitat Zhou Y, Tian C, Jia C. A dose–response meta-analysis of coffee consumption and bladder cancer. Prev Med (Baltim). 2012;55:14–22.CrossRef Zhou Y, Tian C, Jia C. A dose–response meta-analysis of coffee consumption and bladder cancer. Prev Med (Baltim). 2012;55:14–22.CrossRef
26.
Zurück zum Zitat Yu X, Bao Z, Zou J, Dong J. Coffee consumption and risk of cancers: a meta-analysis of cohort studies. BMC Cancer Engl. 2011;11:96.CrossRef Yu X, Bao Z, Zou J, Dong J. Coffee consumption and risk of cancers: a meta-analysis of cohort studies. BMC Cancer Engl. 2011;11:96.CrossRef
27.
Zurück zum Zitat Villanueva CM, Cantor KP, King WD, Jaakkola JJK, Cordier S, Lynch CF, et al. Total and specific fluid consumption as determinants of bladder cancer risk. Int J Cancer. 2006;118:2040–7.PubMedCrossRef Villanueva CM, Cantor KP, King WD, Jaakkola JJK, Cordier S, Lynch CF, et al. Total and specific fluid consumption as determinants of bladder cancer risk. Int J Cancer. 2006;118:2040–7.PubMedCrossRef
28.
Zurück zum Zitat Sala M, Cordier S, Chang-Claude J, Donato F, Escolar-Pujolar A, Fernandez F, et al. Coffee consumption and bladder cancer in nonsmokers: a pooled analysis of case-control studies in European countries. Cancer Causes Control. 2000;11:925–31.PubMedCrossRef Sala M, Cordier S, Chang-Claude J, Donato F, Escolar-Pujolar A, Fernandez F, et al. Coffee consumption and bladder cancer in nonsmokers: a pooled analysis of case-control studies in European countries. Cancer Causes Control. 2000;11:925–31.PubMedCrossRef
29.
Zurück zum Zitat Wu W, Tong Y, Zhao Q, Yu G, Wei X, Lu Q. Coffee consumption and bladder cancer: a meta-analysis of observational studies. Sci Rep. Macmillan Publishers Limited. All rights reserved; 2015; 5. Wu W, Tong Y, Zhao Q, Yu G, Wei X, Lu Q. Coffee consumption and bladder cancer: a meta-analysis of observational studies. Sci Rep. Macmillan Publishers Limited. All rights reserved; 2015; 5.
30.
Zurück zum Zitat Boyle P, Koechlin A, Autier P. Sweetened carbonated beverage consumption and cancer risk: meta-analysis and review. Eur J Cancer Prev. 2014;23:481–90.PubMedCrossRef Boyle P, Koechlin A, Autier P. Sweetened carbonated beverage consumption and cancer risk: meta-analysis and review. Eur J Cancer Prev. 2014;23:481–90.PubMedCrossRef
31.
Zurück zum Zitat Mao Q-Q, Dai Y, Lin Y-W, Qin J, Xie L-P, Zheng X-Y. Milk consumption and bladder cancer risk: a meta-analysis of published epidemiological studies. Nutr Cancer. 2011;63:1263–71.PubMedCrossRef Mao Q-Q, Dai Y, Lin Y-W, Qin J, Xie L-P, Zheng X-Y. Milk consumption and bladder cancer risk: a meta-analysis of published epidemiological studies. Nutr Cancer. 2011;63:1263–71.PubMedCrossRef
32.
Zurück zum Zitat Li Z, Yu J, Miao Q, Sun S, Sun L, Yang H, et al. The association of fish consumption with bladder cancer risk: a meta-analysis. World J Surg Oncol. 2011;9:107.PubMedPubMedCentralCrossRef Li Z, Yu J, Miao Q, Sun S, Sun L, Yang H, et al. The association of fish consumption with bladder cancer risk: a meta-analysis. World J Surg Oncol. 2011;9:107.PubMedPubMedCentralCrossRef
33.
Zurück zum Zitat Li F, An S, Hou L, Chen P, Lei C, Tan W. Red and processed meat intake and risk of bladder cancer: a meta-analysis. Int J Clin Exp Med. 2014;7:2100–10.PubMedPubMedCentral Li F, An S, Hou L, Chen P, Lei C, Tan W. Red and processed meat intake and risk of bladder cancer: a meta-analysis. Int J Clin Exp Med. 2014;7:2100–10.PubMedPubMedCentral
34.
Zurück zum Zitat Pelucchi C, Galeone C, Tramacere I, Bagnardi V, Negri E, Islami F, et al. Alcohol drinking and bladder cancer risk: a meta-analysis. Ann Oncol. 2012;23:1586–93.PubMedCrossRef Pelucchi C, Galeone C, Tramacere I, Bagnardi V, Negri E, Islami F, et al. Alcohol drinking and bladder cancer risk: a meta-analysis. Ann Oncol. 2012;23:1586–93.PubMedCrossRef
35.
Zurück zum Zitat Li F, Zhou Y, Hu R, Hou L, Du Y-J, Zhang X, et al. Egg consumption and risk of bladder cancer: a meta-analysis. Nutr Cancer. 2013;65:538–46.PubMedCrossRef Li F, Zhou Y, Hu R, Hou L, Du Y-J, Zhang X, et al. Egg consumption and risk of bladder cancer: a meta-analysis. Nutr Cancer. 2013;65:538–46.PubMedCrossRef
36.
Zurück zum Zitat Tang J-E, Wang R-J, Zhong H, Yu B, Chen Y. Vitamin A and risk of bladder cancer: a meta-analysis of epidemiological studies. World J Surg Oncol. 2014;12:130.PubMedPubMedCentralCrossRef Tang J-E, Wang R-J, Zhong H, Yu B, Chen Y. Vitamin A and risk of bladder cancer: a meta-analysis of epidemiological studies. World J Surg Oncol. 2014;12:130.PubMedPubMedCentralCrossRef
37.
Zurück zum Zitat Jeon Y-J, Myung S-K, Lee E-H, Kim Y, Chang YJ, Ju W, et al. Effects of beta-carotene supplements on cancer prevention: meta-analysis of randomized controlled trials. Nutr Cancer. 2011;63:1196–207.PubMedCrossRef Jeon Y-J, Myung S-K, Lee E-H, Kim Y, Chang YJ, Ju W, et al. Effects of beta-carotene supplements on cancer prevention: meta-analysis of randomized controlled trials. Nutr Cancer. 2011;63:1196–207.PubMedCrossRef
38.
Zurück zum Zitat Wang Y-Y, Wang X-L, Yu Z-J. Vitamin C and E intake and risk of bladder cancer: a meta-analysis of observational studies. Int J Clin Exp Med. 2014;7:4154–64.PubMedPubMedCentral Wang Y-Y, Wang X-L, Yu Z-J. Vitamin C and E intake and risk of bladder cancer: a meta-analysis of observational studies. Int J Clin Exp Med. 2014;7:4154–64.PubMedPubMedCentral
39.
Zurück zum Zitat Liao Y, Huang JL, Qiu MX, Ma ZW. Impact of serum vitamin D level on risk of bladder cancer: a systemic review and meta-analysis. Tumour Biol. 2015;36:1567–72.PubMedCrossRef Liao Y, Huang JL, Qiu MX, Ma ZW. Impact of serum vitamin D level on risk of bladder cancer: a systemic review and meta-analysis. Tumour Biol. 2015;36:1567–72.PubMedCrossRef
40.
Zurück zum Zitat Chen F, Li Q, Yu Y, Yang W, Shi F, Qu Y. Association of vitamin C, vitamin D, vitamin E and risk of bladder cancer: a dose–response meta-analysis. Sci Rep Nat Publ Group. 2015;5:9599. Chen F, Li Q, Yu Y, Yang W, Shi F, Qu Y. Association of vitamin C, vitamin D, vitamin E and risk of bladder cancer: a dose–response meta-analysis. Sci Rep Nat Publ Group. 2015;5:9599.
41.
Zurück zum Zitat He H, Shui B. Folate intake and risk of bladder cancer: a meta-analysis of epidemiological studies. Int J Food Sci Nutr. 2014;65:286–92.PubMedCrossRef He H, Shui B. Folate intake and risk of bladder cancer: a meta-analysis of epidemiological studies. Int J Food Sci Nutr. 2014;65:286–92.PubMedCrossRef
42.
Zurück zum Zitat Amaral AFS, Cantor KP, Silverman DT, Malats N. Selenium and bladder cancer risk: a meta-analysis. Cancer Epidemiol Biomark Prev. 2010;19:2407–15.CrossRef Amaral AFS, Cantor KP, Silverman DT, Malats N. Selenium and bladder cancer risk: a meta-analysis. Cancer Epidemiol Biomark Prev. 2010;19:2407–15.CrossRef
43.
Zurück zum Zitat Vinceti M, Dennert G, Crespi CM, Zwahlen M, Brinkman M, Zeegers MPA, et al. Selenium for preventing cancer. Cochrane Database Syst Rev. 2014;3:CD005195.PubMedPubMedCentral Vinceti M, Dennert G, Crespi CM, Zwahlen M, Brinkman M, Zeegers MPA, et al. Selenium for preventing cancer. Cochrane Database Syst Rev. 2014;3:CD005195.PubMedPubMedCentral
44.
Zurück zum Zitat Myung S-K, Kim Y, Ju W, Choi HJ, Bae WK. Effects of antioxidant supplements on cancer prevention: meta-analysis of randomized controlled trials. Ann Oncol. 2010;21:166–79.PubMedCrossRef Myung S-K, Kim Y, Ju W, Choi HJ, Bae WK. Effects of antioxidant supplements on cancer prevention: meta-analysis of randomized controlled trials. Ann Oncol. 2010;21:166–79.PubMedCrossRef
45.
Zurück zum Zitat Pelucchi C, Bosetti C, Galeone C, La Vecchia C. Dietary acrylamide and cancer risk: an updated meta-analysis. Int J Cancer. 2015;136:2912–22.PubMedCrossRef Pelucchi C, Bosetti C, Galeone C, La Vecchia C. Dietary acrylamide and cancer risk: an updated meta-analysis. Int J Cancer. 2015;136:2912–22.PubMedCrossRef
46.
Zurück zum Zitat Sun J-W, Zhao L-G, Yang Y, Ma X, Wang Y-Y, Xiang Y-B. Obesity and risk of bladder cancer: a dose–response meta-analysis of 15 cohort studies. PLoS ONE. 2015;10:e0119313.PubMedPubMedCentralCrossRef Sun J-W, Zhao L-G, Yang Y, Ma X, Wang Y-Y, Xiang Y-B. Obesity and risk of bladder cancer: a dose–response meta-analysis of 15 cohort studies. PLoS ONE. 2015;10:e0119313.PubMedPubMedCentralCrossRef
47.
Zurück zum Zitat Qin Q, Xu X, Wang X, Zheng X-Y. Obesity and risk of bladder cancer: a meta-analysis of cohort studies. Asian Pac J Cancer Prev. 2013;14:3117–21.PubMedCrossRef Qin Q, Xu X, Wang X, Zheng X-Y. Obesity and risk of bladder cancer: a meta-analysis of cohort studies. Asian Pac J Cancer Prev. 2013;14:3117–21.PubMedCrossRef
48.
Zurück zum Zitat Puente D, Hartge P, Greiser E, Cantor KP, King WD, Gonzalez CA, et al. A pooled analysis of bladder cancer case–control studies evaluating smoking in men and women. Cancer Causes Control Neth. 2006;17:71–9.CrossRef Puente D, Hartge P, Greiser E, Cantor KP, King WD, Gonzalez CA, et al. A pooled analysis of bladder cancer case–control studies evaluating smoking in men and women. Cancer Causes Control Neth. 2006;17:71–9.CrossRef
49.
Zurück zum Zitat Freedman ND, Silverman DT, Hollenbeck AR, Schatzkin A, Abnet CC. Association between smoking and risk of bladder cancer among men and women. JAMA USA. 2011;306:737–45.CrossRef Freedman ND, Silverman DT, Hollenbeck AR, Schatzkin A, Abnet CC. Association between smoking and risk of bladder cancer among men and women. JAMA USA. 2011;306:737–45.CrossRef
50.
Zurück zum Zitat Brennan P, Bogillot O, Cordier S, Greiser E, Schill W, Vineis P, et al. Cigarette smoking and bladder cancer in men: a pooled analysis of 11 case-control studies. Int J Cancer. 2000;86:289–94.PubMedCrossRef Brennan P, Bogillot O, Cordier S, Greiser E, Schill W, Vineis P, et al. Cigarette smoking and bladder cancer in men: a pooled analysis of 11 case-control studies. Int J Cancer. 2000;86:289–94.PubMedCrossRef
51.
Zurück zum Zitat Brennan P, Bogillot O, Greiser E, Chang-Claude J, Wahrendorf J, Cordier S, et al. The contribution of cigarette smoking to bladder cancer in women (pooled European data). Cancer Causes Control. 2001;12:411–7.PubMedCrossRef Brennan P, Bogillot O, Greiser E, Chang-Claude J, Wahrendorf J, Cordier S, et al. The contribution of cigarette smoking to bladder cancer in women (pooled European data). Cancer Causes Control. 2001;12:411–7.PubMedCrossRef
52.
Zurück zum Zitat Pitard A, Brennan P, Clavel J, Greiser E, Lopez-Abente G, Chang-Claude J, et al. Cigar, pipe, and cigarette smoking and bladder cancer risk in European men. Cancer Causes Control. 2001;12:551–6.PubMedCrossRef Pitard A, Brennan P, Clavel J, Greiser E, Lopez-Abente G, Chang-Claude J, et al. Cigar, pipe, and cigarette smoking and bladder cancer risk in European men. Cancer Causes Control. 2001;12:551–6.PubMedCrossRef
53.
Zurück zum Zitat Cumberbatch MG, Rota M, Catto JWF, La Vecchia C. The role of tobacco smoke in bladder and kidney carcinogenesis: a comparison of exposures and meta-analysis of incidence and mortality risks. Eur Urol 2015;1–9. Cumberbatch MG, Rota M, Catto JWF, La Vecchia C. The role of tobacco smoke in bladder and kidney carcinogenesis: a comparison of exposures and meta-analysis of incidence and mortality risks. Eur Urol 2015;1–9.
54.
Zurück zum Zitat Van Hemelrijck MJJ, Michaud DS, Connolly GN, Kabir Z. Secondhand smoking, 4-aminobiphenyl, and bladder cancer: two meta-analyses. Cancer Epidemiol Biomark Prev. 2009;18:1312–20.CrossRef Van Hemelrijck MJJ, Michaud DS, Connolly GN, Kabir Z. Secondhand smoking, 4-aminobiphenyl, and bladder cancer: two meta-analyses. Cancer Epidemiol Biomark Prev. 2009;18:1312–20.CrossRef
55.
56.
Zurück zum Zitat Keimling M, Behrens G, Schmid D, Jochem C, Leitzmann MF. The association between physical activity and bladder cancer: systematic review and meta-analysis. Br J Cancer. 2014;110:1862–70.PubMedPubMedCentralCrossRef Keimling M, Behrens G, Schmid D, Jochem C, Leitzmann MF. The association between physical activity and bladder cancer: systematic review and meta-analysis. Br J Cancer. 2014;110:1862–70.PubMedPubMedCentralCrossRef
57.
Zurück zum Zitat Turati F, Pelucchi C, Galeone C, Decarli A, La Vecchia C. Personal hair dye use and bladder cancer: a meta-analysis. Ann Epidemiol. 2014;24:151–9.PubMedCrossRef Turati F, Pelucchi C, Galeone C, Decarli A, La Vecchia C. Personal hair dye use and bladder cancer: a meta-analysis. Ann Epidemiol. 2014;24:151–9.PubMedCrossRef
58.
Zurück zum Zitat Kelsh MA, Alexander DD, Kalmes RM, Buffler PA. Personal use of hair dyes and risk of bladder cancer: a meta-analysis of epidemiologic data. Cancer Causes Control. 2008;19:549–58.PubMedCrossRef Kelsh MA, Alexander DD, Kalmes RM, Buffler PA. Personal use of hair dyes and risk of bladder cancer: a meta-analysis of epidemiologic data. Cancer Causes Control. 2008;19:549–58.PubMedCrossRef
59.
Zurück zum Zitat Huncharek M, Kupelnick B. Personal use of hair dyes and the risk of bladder cancer: results of a meta-analysis. Public Health Rep USA. 2005;120:31–8. Huncharek M, Kupelnick B. Personal use of hair dyes and the risk of bladder cancer: results of a meta-analysis. Public Health Rep USA. 2005;120:31–8.
60.
Zurück zum Zitat Takkouche B, Etminan M, Montes-Martínez A. Personal use of hair dyes and risk of cancer: a meta-analysis. JAMA. 2005;293:2516–25.PubMedCrossRef Takkouche B, Etminan M, Montes-Martínez A. Personal use of hair dyes and risk of cancer: a meta-analysis. JAMA. 2005;293:2516–25.PubMedCrossRef
61.
Zurück zum Zitat Cumberbatch MGK, Cox A, Teare D, Catto JWF. Contemporary occupational carcinogen exposure and bladder cancer. JAMA Oncol. 2015;1:1282–90.PubMedCrossRef Cumberbatch MGK, Cox A, Teare D, Catto JWF. Contemporary occupational carcinogen exposure and bladder cancer. JAMA Oncol. 2015;1:1282–90.PubMedCrossRef
62.
Zurück zum Zitat Reulen RC, Kellen E, Buntinx F, Brinkman M, Zeegers MP. A meta-analysis on the association between bladder cancer and occupation. Scand J Urol Nephrol Suppl. 2008;42:64–78.CrossRef Reulen RC, Kellen E, Buntinx F, Brinkman M, Zeegers MP. A meta-analysis on the association between bladder cancer and occupation. Scand J Urol Nephrol Suppl. 2008;42:64–78.CrossRef
63.
Zurück zum Zitat Kogevinas M, ’t Mannetje A, Cordier S, Ranft U, González CA, Vineis P, et al. Occupation and bladder cancer among men in Western Europe. Cancer Causes Control. 2003;14:907–14.PubMedCrossRef Kogevinas M, ’t Mannetje A, Cordier S, Ranft U, González CA, Vineis P, et al. Occupation and bladder cancer among men in Western Europe. Cancer Causes Control. 2003;14:907–14.PubMedCrossRef
64.
Zurück zum Zitat Mannetje A, Kogevinas M, Chang-Claude J, Cordier S, Gonzalez CA, Hours M, et al. Occupation and bladder cancer in European women. Cancer Causes Control. 1999;10:209–17.PubMedCrossRef Mannetje A, Kogevinas M, Chang-Claude J, Cordier S, Gonzalez CA, Hours M, et al. Occupation and bladder cancer in European women. Cancer Causes Control. 1999;10:209–17.PubMedCrossRef
65.
Zurück zum Zitat Clavel J, Cordier S, Boccon-Gibod L, Hemon D. Tobacco and bladder cancer in males: increased risk for inhalers and smokers of black tobacco. Int J Cancer. 1989;44:605–10.PubMedCrossRef Clavel J, Cordier S, Boccon-Gibod L, Hemon D. Tobacco and bladder cancer in males: increased risk for inhalers and smokers of black tobacco. Int J Cancer. 1989;44:605–10.PubMedCrossRef
66.
Zurück zum Zitat D’Avanzo B, Negri E, La Vecchia C, Gramenzi A, Bianchi C, Franceschi S, et al. Cigarette smoking and bladder cancer. Eur J Cancer. 1990;26:714–8.PubMedCrossRef D’Avanzo B, Negri E, La Vecchia C, Gramenzi A, Bianchi C, Franceschi S, et al. Cigarette smoking and bladder cancer. Eur J Cancer. 1990;26:714–8.PubMedCrossRef
67.
Zurück zum Zitat D’Avanzo B, La Vecchia C, Negri E, Decarli A, Benichou J. Attributable risks for bladder cancer in northern Italy. Ann Epidemiol. 1995;5:427–31.PubMedCrossRef D’Avanzo B, La Vecchia C, Negri E, Decarli A, Benichou J. Attributable risks for bladder cancer in northern Italy. Ann Epidemiol. 1995;5:427–31.PubMedCrossRef
68.
Zurück zum Zitat Iscovich J, Castelletto R, Esteve J, Munoz N, Colanzi R, Coronel A, et al. Tobacco smoking, occupational exposure and bladder cancer in Argentina. Int J Cancer. 1987;40:734–40.PubMedCrossRef Iscovich J, Castelletto R, Esteve J, Munoz N, Colanzi R, Coronel A, et al. Tobacco smoking, occupational exposure and bladder cancer in Argentina. Int J Cancer. 1987;40:734–40.PubMedCrossRef
69.
Zurück zum Zitat Momas I, Daures JP, Festy B, Bontoux J. Gremy F (1994) Bladder cancer and black tobacco cigarette smoking Some results from a French case-control study. Eur J Epidemiol. 1994;10:599–604.PubMedCrossRef Momas I, Daures JP, Festy B, Bontoux J. Gremy F (1994) Bladder cancer and black tobacco cigarette smoking Some results from a French case-control study. Eur J Epidemiol. 1994;10:599–604.PubMedCrossRef
70.
Zurück zum Zitat De Stefani E, Correa P, Fierro L, Fontham E, Chen V, Zavala D. Black tobacco, mate, and bladder cancer. A case–control study from Uruguay. Cancer. 1991;67:536–40.PubMedCrossRef De Stefani E, Correa P, Fierro L, Fontham E, Chen V, Zavala D. Black tobacco, mate, and bladder cancer. A case–control study from Uruguay. Cancer. 1991;67:536–40.PubMedCrossRef
71.
Zurück zum Zitat Samanic C, Kogevinas M, Dosemeci M, Malats N, Real FX, Garcia-Closas M, et al. Smoking and bladder cancer in Spain: effects of tobacco type, timing, environmental tobacco smoke, and gender. Cancer Epidemiol Biomark Prev. 2006;15:1348–54.CrossRef Samanic C, Kogevinas M, Dosemeci M, Malats N, Real FX, Garcia-Closas M, et al. Smoking and bladder cancer in Spain: effects of tobacco type, timing, environmental tobacco smoke, and gender. Cancer Epidemiol Biomark Prev. 2006;15:1348–54.CrossRef
72.
Zurück zum Zitat Cole P, Monson RR, Haning H, Friedell GH. Smoking and cancer f the lower urinary tract. N Engl J Med. 1971;284:129–34.PubMedCrossRef Cole P, Monson RR, Haning H, Friedell GH. Smoking and cancer f the lower urinary tract. N Engl J Med. 1971;284:129–34.PubMedCrossRef
73.
Zurück zum Zitat Morrison AS, Buring JE, Verhoek WG, Aoki K, Leck I, Ohno Y, et al. An international study of smoking and bladder cancer. J Urol. 1984;131:650–4.PubMed Morrison AS, Buring JE, Verhoek WG, Aoki K, Leck I, Ohno Y, et al. An international study of smoking and bladder cancer. J Urol. 1984;131:650–4.PubMed
74.
Zurück zum Zitat Zeegers MPA, Goldbohm RA, van den Brandt PA. A prospective study on active and environmental tobacco smoking and bladder cancer risk (The Netherlands). Cancer Causes Control. 2002;13:83–90.PubMedCrossRef Zeegers MPA, Goldbohm RA, van den Brandt PA. A prospective study on active and environmental tobacco smoking and bladder cancer risk (The Netherlands). Cancer Causes Control. 2002;13:83–90.PubMedCrossRef
75.
Zurück zum Zitat Lopez-Abente G, Gonzalez CA, Errezola M, Escolar A, Izarzugaza I, Nebot M, et al. Tobacco smoke inhalation pattern, tobacco type, and bladder cancer in Spain. Am J Epidemiol. 1991;134:830–9.PubMed Lopez-Abente G, Gonzalez CA, Errezola M, Escolar A, Izarzugaza I, Nebot M, et al. Tobacco smoke inhalation pattern, tobacco type, and bladder cancer in Spain. Am J Epidemiol. 1991;134:830–9.PubMed
76.
Zurück zum Zitat Burch JD, Rohan TE, Howe GR, Risch HA, Hill GB, Steele R, et al. Risk of bladder cancer by source and type of tobacco exposure: a case–control study. Int J Cancer. 1989;44:622–8.PubMedCrossRef Burch JD, Rohan TE, Howe GR, Risch HA, Hill GB, Steele R, et al. Risk of bladder cancer by source and type of tobacco exposure: a case–control study. Int J Cancer. 1989;44:622–8.PubMedCrossRef
77.
Zurück zum Zitat Hartge P, Silverman D, Hoover R, Schairer C, Altman R, Austin D, et al. Changing cigarette habits and bladder cancer risk: a case–control study. J Natl Cancer Inst. 1987;78:1119–25.PubMed Hartge P, Silverman D, Hoover R, Schairer C, Altman R, Austin D, et al. Changing cigarette habits and bladder cancer risk: a case–control study. J Natl Cancer Inst. 1987;78:1119–25.PubMed
78.
Zurück zum Zitat Castelao JE, Yuan JM, Skipper PL, Tannenbaum SR, Gago-Dominguez M, Crowder JS, et al. Gender- and smoking-related bladder cancer risk. J Natl Cancer Inst. 2001;93:538–45.PubMedCrossRef Castelao JE, Yuan JM, Skipper PL, Tannenbaum SR, Gago-Dominguez M, Crowder JS, et al. Gender- and smoking-related bladder cancer risk. J Natl Cancer Inst. 2001;93:538–45.PubMedCrossRef
79.
Zurück zum Zitat Howe GR, Burch JD, Miller AB, Cook GM, Esteve J, Morrison B, et al. Tobacco use, occupation, coffee, various nutrients, and bladder cancer. J Natl Cancer Inst. 1980;64:701–13.PubMed Howe GR, Burch JD, Miller AB, Cook GM, Esteve J, Morrison B, et al. Tobacco use, occupation, coffee, various nutrients, and bladder cancer. J Natl Cancer Inst. 1980;64:701–13.PubMed
80.
Zurück zum Zitat Lockwood K. On the etiology of bladder tumors in Kobenhavn-Frederiksberg. An inquiry of 369 patients and 369 controls. Acta Pathol Microbiol. Scand. Suppl. Not Available; 1961;51(Suppl 1):1–166. Lockwood K. On the etiology of bladder tumors in Kobenhavn-Frederiksberg. An inquiry of 369 patients and 369 controls. Acta Pathol Microbiol. Scand. Suppl. Not Available; 1961;51(Suppl 1):1–166.
81.
Zurück zum Zitat Hein DW. Molecular genetics and function of NAT1 and NAT2: role in aromatic amine metabolism and carcinogenesis. Mutat Res. 2002;506–507:65–77.PubMedCrossRef Hein DW. Molecular genetics and function of NAT1 and NAT2: role in aromatic amine metabolism and carcinogenesis. Mutat Res. 2002;506–507:65–77.PubMedCrossRef
82.
Zurück zum Zitat Centers for Disease Control and Prevention. How tobacco smoke causes disease: The biology and behavioral basis for smoking-attributable disease: A report of the surgeon general. Atlanta (GA); 2010. Centers for Disease Control and Prevention. How tobacco smoke causes disease: The biology and behavioral basis for smoking-attributable disease: A report of the surgeon general. Atlanta (GA); 2010.
83.
Zurück zum Zitat Pelucchi C, Bosetti C, Negri E, Malvezzi M, La Vecchia C. Mechanisms of disease: The epidemiology of bladder cancer. Nat Clin Pract Urol. 2006;3:327–40.PubMedCrossRef Pelucchi C, Bosetti C, Negri E, Malvezzi M, La Vecchia C. Mechanisms of disease: The epidemiology of bladder cancer. Nat Clin Pract Urol. 2006;3:327–40.PubMedCrossRef
84.
Zurück zum Zitat Brinkman M, Zeegers MP. Nutrition, total fluid and bladder cancer. Scand J Urol Nephrol Suppl. 2008;42:25–36.CrossRef Brinkman M, Zeegers MP. Nutrition, total fluid and bladder cancer. Scand J Urol Nephrol Suppl. 2008;42:25–36.CrossRef
85.
Zurück zum Zitat Liu RH. Potential synergy of phytochemicals in cancer prevention: mechanism of action. J Nutr. 2004;134:3479S–85S.PubMed Liu RH. Potential synergy of phytochemicals in cancer prevention: mechanism of action. J Nutr. 2004;134:3479S–85S.PubMed
86.
Zurück zum Zitat Talalay P, Fahey JW. Phytochemicals from cruciferous plants protect against cancer by modulating carcinogen metabolism. J Nutr. 2001;131:3027S–33S.PubMed Talalay P, Fahey JW. Phytochemicals from cruciferous plants protect against cancer by modulating carcinogen metabolism. J Nutr. 2001;131:3027S–33S.PubMed
87.
Zurück zum Zitat Kirk SF, Cade JE, Barrett JH, Conner M. Diet and lifestyle characteristics associated with dietary supplement use in women. Public Health Nutr. 1999;2:69–73.PubMedCrossRef Kirk SF, Cade JE, Barrett JH, Conner M. Diet and lifestyle characteristics associated with dietary supplement use in women. Public Health Nutr. 1999;2:69–73.PubMedCrossRef
88.
Zurück zum Zitat Nutting CM, Huddart RA. Retinoids in the prevention of bladder cancer. Expert Rev Anticancer Ther. 2001;1:541–5.PubMedCrossRef Nutting CM, Huddart RA. Retinoids in the prevention of bladder cancer. Expert Rev Anticancer Ther. 2001;1:541–5.PubMedCrossRef
89.
Zurück zum Zitat International Agency for Research on Cancer. IARC Handbook of Cancer Prevention Volume 2: Carotenoids. Lyon, France: International Agency for Research on Cancer; 1998. International Agency for Research on Cancer. IARC Handbook of Cancer Prevention Volume 2: Carotenoids. Lyon, France: International Agency for Research on Cancer; 1998.
90.
91.
Zurück zum Zitat Jiang Q. Natural forms of vitamin E: metabolism, antioxidant, and anti-inflammatory activities and their role in disease prevention and therapy. Free Radic Biol Med. 2014;72:76–90.PubMedPubMedCentralCrossRef Jiang Q. Natural forms of vitamin E: metabolism, antioxidant, and anti-inflammatory activities and their role in disease prevention and therapy. Free Radic Biol Med. 2014;72:76–90.PubMedPubMedCentralCrossRef
92.
Zurück zum Zitat Balkwill F, Mantovani A. Inflammation and cancer: back to Virchow? Lancet (Lond). 2001;357:539–45.CrossRef Balkwill F, Mantovani A. Inflammation and cancer: back to Virchow? Lancet (Lond). 2001;357:539–45.CrossRef
93.
Zurück zum Zitat Das S. Vitamin E in the genesis and prevention of cancer. A review. Acta Oncol. 1994;33:615–9.PubMedCrossRef Das S. Vitamin E in the genesis and prevention of cancer. A review. Acta Oncol. 1994;33:615–9.PubMedCrossRef
94.
Zurück zum Zitat Jackson MI, Combs GF. Selenium and anticarcinogenesis: underlying mechanisms. Curr Opin Clin Nutr Metab Care. 2008;11:718–26.PubMedCrossRef Jackson MI, Combs GF. Selenium and anticarcinogenesis: underlying mechanisms. Curr Opin Clin Nutr Metab Care. 2008;11:718–26.PubMedCrossRef
95.
Zurück zum Zitat Mosby TT, Cosgrove M, Sarkardei S, Platt KL, Kaina B. Nutrition in adult and childhood cancer: role of carcinogens and anti-carcinogens. Anticancer Res. 2012;32:4171–92.PubMed Mosby TT, Cosgrove M, Sarkardei S, Platt KL, Kaina B. Nutrition in adult and childhood cancer: role of carcinogens and anti-carcinogens. Anticancer Res. 2012;32:4171–92.PubMed
96.
Zurück zum Zitat Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis. Circulation. 2010;121:2271–83.PubMedPubMedCentralCrossRef Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis. Circulation. 2010;121:2271–83.PubMedPubMedCentralCrossRef
97.
Zurück zum Zitat Baena Ruiz R, Salinas Hernández P. Diet and cancer: risk factors and epidemiological evidence. Maturitas. 2014;77:202–8.PubMedCrossRef Baena Ruiz R, Salinas Hernández P. Diet and cancer: risk factors and epidemiological evidence. Maturitas. 2014;77:202–8.PubMedCrossRef
98.
Zurück zum Zitat Choi SW, Mason JB. Folate and carcinogenesis: an integrated scheme. J Nutr. 2000;130:129–32.PubMed Choi SW, Mason JB. Folate and carcinogenesis: an integrated scheme. J Nutr. 2000;130:129–32.PubMed
99.
Zurück zum Zitat Duthie SJ, Narayanan S, Brand GM, Pirie L, Grant G. Impact of folate deficiency on DNA stability. J Nutr. 2002;132:2444S–9S.PubMed Duthie SJ, Narayanan S, Brand GM, Pirie L, Grant G. Impact of folate deficiency on DNA stability. J Nutr. 2002;132:2444S–9S.PubMed
100.
101.
Zurück zum Zitat Lee JE, Li H, Chan AT, Hollis BW, Lee I-M, Stampfer MJ, et al. Circulating levels of vitamin D and colon and rectal cancer: the Physicians’ Health Study and a meta-analysis of prospective studies. Cancer Prev Res (Phila). 2011;4:735–43.CrossRef Lee JE, Li H, Chan AT, Hollis BW, Lee I-M, Stampfer MJ, et al. Circulating levels of vitamin D and colon and rectal cancer: the Physicians’ Health Study and a meta-analysis of prospective studies. Cancer Prev Res (Phila). 2011;4:735–43.CrossRef
102.
103.
Zurück zum Zitat Feldman D, Krishnan AV, Swami S, Giovannucci E, Feldman BJ. The role of vitamin D in reducing cancer risk and progression. Nat Rev Cancer. 2014;14:342–57.PubMedCrossRef Feldman D, Krishnan AV, Swami S, Giovannucci E, Feldman BJ. The role of vitamin D in reducing cancer risk and progression. Nat Rev Cancer. 2014;14:342–57.PubMedCrossRef
104.
Zurück zum Zitat Silberstein JL, Parsons JK. Evidence-based principles of bladder cancer and diet. Urology. 2010;75:340–6.PubMedCrossRef Silberstein JL, Parsons JK. Evidence-based principles of bladder cancer and diet. Urology. 2010;75:340–6.PubMedCrossRef
105.
Zurück zum Zitat Villanueva CM, Fernández F, Malats N, Grimalt JO, Kogevinas M. Meta-analysis of studies on individual consumption of chlorinated drinking water and bladder cancer. J Epidemiol Community Health. 2003;57:166–73.PubMedPubMedCentralCrossRef Villanueva CM, Fernández F, Malats N, Grimalt JO, Kogevinas M. Meta-analysis of studies on individual consumption of chlorinated drinking water and bladder cancer. J Epidemiol Community Health. 2003;57:166–73.PubMedPubMedCentralCrossRef
106.
Zurück zum Zitat Costet N, Villanueva CM, Jaakkola JJK, Kogevinas M, Cantor KP, King WD, et al. Water disinfection by-products and bladder cancer: Is there a European specificity? A pooled and meta-analysis of European case–control studies. Occup Environ Med. 2011;68:379–85.PubMedCrossRef Costet N, Villanueva CM, Jaakkola JJK, Kogevinas M, Cantor KP, King WD, et al. Water disinfection by-products and bladder cancer: Is there a European specificity? A pooled and meta-analysis of European case–control studies. Occup Environ Med. 2011;68:379–85.PubMedCrossRef
107.
Zurück zum Zitat Tsuji JS, Alexander DD, Perez V, Mink PJ. Arsenic exposure and bladder cancer: quantitative assessment of studies in human populations to detect risks at low doses. Toxicology. 2014;317:17–30.PubMedCrossRef Tsuji JS, Alexander DD, Perez V, Mink PJ. Arsenic exposure and bladder cancer: quantitative assessment of studies in human populations to detect risks at low doses. Toxicology. 2014;317:17–30.PubMedCrossRef
108.
Zurück zum Zitat Chu H-A, Crawford-Brown DJ. Inorganic arsenic in drinking water and bladder cancer: a meta-analysis for dose–response assessment. Int J Environ Res Public Health. 2006;3:316–22.PubMedCrossRef Chu H-A, Crawford-Brown DJ. Inorganic arsenic in drinking water and bladder cancer: a meta-analysis for dose–response assessment. Int J Environ Res Public Health. 2006;3:316–22.PubMedCrossRef
109.
Zurück zum Zitat Rogers CJ, Colbert LH, Greiner JW, Perkins SN, Hursting SD. Physical activity and cancer prevention: pathways and targets for intervention. Sports Med. 2008;38:271–96.PubMedCrossRef Rogers CJ, Colbert LH, Greiner JW, Perkins SN, Hursting SD. Physical activity and cancer prevention: pathways and targets for intervention. Sports Med. 2008;38:271–96.PubMedCrossRef
110.
Zurück zum Zitat Letašiová S, Medve’ová A, Šovčíková A, Dušinská M, Volkovová K, Mosoiu C, et al. Bladder cancer, a review of the environmental risk factors. Environ Health. 2012;11(Suppl 1):S11.PubMedPubMedCentralCrossRef Letašiová S, Medve’ová A, Šovčíková A, Dušinská M, Volkovová K, Mosoiu C, et al. Bladder cancer, a review of the environmental risk factors. Environ Health. 2012;11(Suppl 1):S11.PubMedPubMedCentralCrossRef
111.
Zurück zum Zitat Alavanja MCR, Bonner MR. Occupational pesticide exposures and cancer risk: a review. J Toxicol Environ Health B Crit Rev. 2012;15:238–63.PubMedCrossRef Alavanja MCR, Bonner MR. Occupational pesticide exposures and cancer risk: a review. J Toxicol Environ Health B Crit Rev. 2012;15:238–63.PubMedCrossRef
112.
Zurück zum Zitat Ntzani E, Chondrogiorgi M, Ntritsos G, Evangelou E, Tzoulaki I. Literature re view on epidemiological studies linking exposure to pesticides and health effect. EFSA supporting publication 2013:EN-497. 2013. Ntzani E, Chondrogiorgi M, Ntritsos G, Evangelou E, Tzoulaki I. Literature re view on epidemiological studies linking exposure to pesticides and health effect. EFSA supporting publication 2013:EN-497. 2013.
113.
Zurück zum Zitat IAC Monographs on the Evaluation of Carcinogenic Risks to Humans, Volume 53, Occupational Exposures in Insecticide Application, and Some Pesticides. Lyon, France; 1991. IAC Monographs on the Evaluation of Carcinogenic Risks to Humans, Volume 53, Occupational Exposures in Insecticide Application, and Some Pesticides. Lyon, France; 1991.
114.
115.
Zurück zum Zitat Berrigan D, Dodd K, Troiano RP, Krebs-Smith SM, Barbash RB. Patterns of health behavior in U.S. adults. Prev Med (Baltim). 2003;36:615–23.CrossRef Berrigan D, Dodd K, Troiano RP, Krebs-Smith SM, Barbash RB. Patterns of health behavior in U.S. adults. Prev Med (Baltim). 2003;36:615–23.CrossRef
116.
Zurück zum Zitat Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60.PubMedPubMedCentralCrossRef Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–60.PubMedPubMedCentralCrossRef
118.
Zurück zum Zitat Yusuf PS, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study. Lancet. 2004;364:937–52.PubMedCrossRef Yusuf PS, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study. Lancet. 2004;364:937–52.PubMedCrossRef
119.
Zurück zum Zitat Danaei G, Ding EL, Mozaffarian D, Taylor B, Rehm J, Murray CJL, et al. The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors. PLoS Med. 2009;6:e1000058.PubMedPubMedCentralCrossRef Danaei G, Ding EL, Mozaffarian D, Taylor B, Rehm J, Murray CJL, et al. The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors. PLoS Med. 2009;6:e1000058.PubMedPubMedCentralCrossRef
120.
Zurück zum Zitat Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. Am J Clin Nutr. 2003;78:559S–69S.PubMed Riboli E, Norat T. Epidemiologic evidence of the protective effect of fruit and vegetables on cancer risk. Am J Clin Nutr. 2003;78:559S–69S.PubMed
121.
Zurück zum Zitat Liu B, Mao Q, Lin Y, Zhou F, Xie L. The association of cruciferous vegetables intake and risk of bladder cancer: a meta-analysis. World J Urol. 2013;31:127–33.PubMedCrossRef Liu B, Mao Q, Lin Y, Zhou F, Xie L. The association of cruciferous vegetables intake and risk of bladder cancer: a meta-analysis. World J Urol. 2013;31:127–33.PubMedCrossRef
122.
Zurück zum Zitat Vieira AR, Vingeliene S, Chan DSM, Aune D, Abar L, Navarro Rosenblatt D, et al. Fruits, vegetables, and bladder cancer risk: a systematic review and meta-analysis. Cancer Med. 2015;4:136–46.PubMedCrossRef Vieira AR, Vingeliene S, Chan DSM, Aune D, Abar L, Navarro Rosenblatt D, et al. Fruits, vegetables, and bladder cancer risk: a systematic review and meta-analysis. Cancer Med. 2015;4:136–46.PubMedCrossRef
123.
Zurück zum Zitat Liu H, Wang X-C, Hu G-H, Guo Z-F, Lai P, Xu L, et al. Fruit and vegetable consumption and risk of bladder cancer. Eur J Cancer Prev. 2015;24:508–16.PubMedCrossRef Liu H, Wang X-C, Hu G-H, Guo Z-F, Lai P, Xu L, et al. Fruit and vegetable consumption and risk of bladder cancer. Eur J Cancer Prev. 2015;24:508–16.PubMedCrossRef
124.
Zurück zum Zitat Xu C, Zeng X-T, Liu T-Z, Zhang C, Yang Z-H, Li S, et al. Fruits and vegetables intake and risk of bladder cancer: a PRISMA-compliant systematic review and dose–response meta-analysis of prospective cohort studies. Medicine (Baltimore). 2015;94:e759.CrossRef Xu C, Zeng X-T, Liu T-Z, Zhang C, Yang Z-H, Li S, et al. Fruits and vegetables intake and risk of bladder cancer: a PRISMA-compliant systematic review and dose–response meta-analysis of prospective cohort studies. Medicine (Baltimore). 2015;94:e759.CrossRef
125.
Zurück zum Zitat Zeegers MP, Tan FE, Goldbohm RA, van den Brandt PA. Are coffee and tea consumption associated with urinary tract cancer risk? A systematic review and meta-analysis. Int J Epidemiol. 2001;30:353–62.PubMedCrossRef Zeegers MP, Tan FE, Goldbohm RA, van den Brandt PA. Are coffee and tea consumption associated with urinary tract cancer risk? A systematic review and meta-analysis. Int J Epidemiol. 2001;30:353–62.PubMedCrossRef
126.
Zurück zum Zitat Zhang Y-F, Xu Q, Lu J, Wang P, Zhang H-W, Zhou L, et al. Tea consumption and the incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Eur J Cancer Prev. 2015;24:353–62.PubMedCrossRef Zhang Y-F, Xu Q, Lu J, Wang P, Zhang H-W, Zhou L, et al. Tea consumption and the incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Eur J Cancer Prev. 2015;24:353–62.PubMedCrossRef
127.
Zurück zum Zitat Wu S, Li F, Huang X, Hua Q, Huang T, Liu Z, et al. The association of tea consumption with bladder cancer risk: a meta-analysis. Asia Pac J Clin Nutr. 2013;22:128–37.PubMed Wu S, Li F, Huang X, Hua Q, Huang T, Liu Z, et al. The association of tea consumption with bladder cancer risk: a meta-analysis. Asia Pac J Clin Nutr. 2013;22:128–37.PubMed
128.
Zurück zum Zitat Wang X, Lin Y-W, Wang S, Wu J, Mao Q-Q, Zheng X-Y, et al. A meta-analysis of tea consumption and the risk of bladder cancer. Urol Int. 2013;90:10–6.PubMedCrossRef Wang X, Lin Y-W, Wang S, Wu J, Mao Q-Q, Zheng X-Y, et al. A meta-analysis of tea consumption and the risk of bladder cancer. Urol Int. 2013;90:10–6.PubMedCrossRef
130.
131.
132.
Zurück zum Zitat Pelucchi C, La Vecchia C. Alcohol, coffee, and bladder cancer risk: a review of epidemiological studies. Eur J Cancer Prev. 2009;18:62–8.PubMedCrossRef Pelucchi C, La Vecchia C. Alcohol, coffee, and bladder cancer risk: a review of epidemiological studies. Eur J Cancer Prev. 2009;18:62–8.PubMedCrossRef
133.
Zurück zum Zitat Zhang Z-H, Yang L-S, Sun Y-H. The association between milk consumption and bladder cancer risk: appraisal of a recent meta-analysis. Nutr Cancer. 2012;64:1288–9.PubMedCrossRef Zhang Z-H, Yang L-S, Sun Y-H. The association between milk consumption and bladder cancer risk: appraisal of a recent meta-analysis. Nutr Cancer. 2012;64:1288–9.PubMedCrossRef
135.
Zurück zum Zitat Li F, An S, Zhou Y, Liang Z, Jiao Z, Jing Y, et al. Milk and dairy consumption and risk of bladder cancer: a meta-analysis. Urology. 2011;78:1298–305.PubMedCrossRef Li F, An S, Zhou Y, Liang Z, Jiao Z, Jing Y, et al. Milk and dairy consumption and risk of bladder cancer: a meta-analysis. Urology. 2011;78:1298–305.PubMedCrossRef
136.
Zurück zum Zitat Wang C, Jiang H. Meat intake and risk of bladder cancer: a meta-analysis. Med Oncol. 2012;29:848–55.PubMedCrossRef Wang C, Jiang H. Meat intake and risk of bladder cancer: a meta-analysis. Med Oncol. 2012;29:848–55.PubMedCrossRef
137.
Zurück zum Zitat Mao Q, Lin Y, Zheng X, Qin J, Yang K, Xie L. A meta-analysis of alcohol intake and risk of bladder cancer. Cancer Causes Control. 2010;21:1843–50.PubMedCrossRef Mao Q, Lin Y, Zheng X, Qin J, Yang K, Xie L. A meta-analysis of alcohol intake and risk of bladder cancer. Cancer Causes Control. 2010;21:1843–50.PubMedCrossRef
138.
Zurück zum Zitat de Menezes RF, Bergmann A, Thuler LCS. Alcohol consumption and risk of cancer: a systematic literature review. Asian Pac J Cancer Prev. 2013;14:4965–72.PubMedCrossRef de Menezes RF, Bergmann A, Thuler LCS. Alcohol consumption and risk of cancer: a systematic literature review. Asian Pac J Cancer Prev. 2013;14:4965–72.PubMedCrossRef
139.
140.
Zurück zum Zitat Zeegers MP, Tan FE, Verhagen AP, Weijenberg MP, van den Brandt PA. Elevated risk of cancer of the urinary tract for alcohol drinkers: a meta-analysis. Cancer Causes Control. 1999;10:445–51.PubMedCrossRef Zeegers MP, Tan FE, Verhagen AP, Weijenberg MP, van den Brandt PA. Elevated risk of cancer of the urinary tract for alcohol drinkers: a meta-analysis. Cancer Causes Control. 1999;10:445–51.PubMedCrossRef
141.
Zurück zum Zitat Fang D, Tan F, Wang C, Zhu X, Xie L. Egg intake and bladder cancer risk: a meta-analysis. Exp Ther Med. 2012;4:906–12.PubMedPubMedCentral Fang D, Tan F, Wang C, Zhu X, Xie L. Egg intake and bladder cancer risk: a meta-analysis. Exp Ther Med. 2012;4:906–12.PubMedPubMedCentral
142.
Zurück zum Zitat Musa-Veloso K, Card JW, Wong AW, Cooper DA. Influence of observational study design on the interpretation of cancer risk reduction by carotenoids. Nutr Rev. 2009;67:527–45.PubMedCrossRef Musa-Veloso K, Card JW, Wong AW, Cooper DA. Influence of observational study design on the interpretation of cancer risk reduction by carotenoids. Nutr Rev. 2009;67:527–45.PubMedCrossRef
143.
Zurück zum Zitat Coulter ID, Hardy ML, Morton SC, Hilton LG, Tu W, Valentine D, et al. Antioxidants vitamin C and vitamin e for the prevention and treatment of cancer. J Gen Intern Med. 2006;21:735–44.PubMedPubMedCentralCrossRef Coulter ID, Hardy ML, Morton SC, Hilton LG, Tu W, Valentine D, et al. Antioxidants vitamin C and vitamin e for the prevention and treatment of cancer. J Gen Intern Med. 2006;21:735–44.PubMedPubMedCentralCrossRef
144.
Zurück zum Zitat MacLean CH, Newberry SJ, Mojica WA, Khanna P, Issa AM, Suttorp MJ, et al. Effects of omega-3 fatty acids on cancer risk: a systematic review. JAMA. 2006;295:403–15.PubMedCrossRef MacLean CH, Newberry SJ, Mojica WA, Khanna P, Issa AM, Suttorp MJ, et al. Effects of omega-3 fatty acids on cancer risk: a systematic review. JAMA. 2006;295:403–15.PubMedCrossRef
145.
Zurück zum Zitat Mao S, Huang S. Zinc and copper levels in bladder cancer: a systematic review and meta-analysis. Biol Trace Elem Res. 2013;153:5–10.PubMedCrossRef Mao S, Huang S. Zinc and copper levels in bladder cancer: a systematic review and meta-analysis. Biol Trace Elem Res. 2013;153:5–10.PubMedCrossRef
146.
Zurück zum Zitat Psaltopoulou T, Kosti RI, Haidopoulos D, Dimopoulos M, Panagiotakos DB. Olive oil intake is inversely related to cancer prevalence: a systematic review and a meta-analysis of 13,800 patients and 23,340 controls in 19 observational studies. Lipids Health Dis. 2011;10:127.PubMedPubMedCentralCrossRef Psaltopoulou T, Kosti RI, Haidopoulos D, Dimopoulos M, Panagiotakos DB. Olive oil intake is inversely related to cancer prevalence: a systematic review and a meta-analysis of 13,800 patients and 23,340 controls in 19 observational studies. Lipids Health Dis. 2011;10:127.PubMedPubMedCentralCrossRef
147.
Zurück zum Zitat Lotan Y, Daudon M, Bruyère F, Talaska G, Strippoli G, Johnson RJ, et al. Impact of fluid intake in the prevention of urinary system diseases: a brief review. Curr Opin Nephrol Hypertens. 2013;22(Suppl 1):S1–10.PubMedCrossRef Lotan Y, Daudon M, Bruyère F, Talaska G, Strippoli G, Johnson RJ, et al. Impact of fluid intake in the prevention of urinary system diseases: a brief review. Curr Opin Nephrol Hypertens. 2013;22(Suppl 1):S1–10.PubMedCrossRef
148.
149.
Zurück zum Zitat Zeegers MP, Tan FE, Dorant E, van Den Brandt PA. The impact of characteristics of cigarette smoking on urinary tract cancer risk: a meta-analysis of epidemiologic studies. Cancer. 2000;89:630–9.PubMedCrossRef Zeegers MP, Tan FE, Dorant E, van Den Brandt PA. The impact of characteristics of cigarette smoking on urinary tract cancer risk: a meta-analysis of epidemiologic studies. Cancer. 2000;89:630–9.PubMedCrossRef
150.
Zurück zum Zitat Crivelli JJ, Xylinas E, Kluth LA, Rieken M, Rink M, Shariat SF. Effect of smoking on outcomes of urothelial carcinoma: a systematic review of the literature. Eur Urol. 2014;65:742–54.CrossRefPubMed Crivelli JJ, Xylinas E, Kluth LA, Rieken M, Rink M, Shariat SF. Effect of smoking on outcomes of urothelial carcinoma: a systematic review of the literature. Eur Urol. 2014;65:742–54.CrossRefPubMed
151.
Zurück zum Zitat Sasco AJ, Secretan MB, Straif K. Tobacco smoking and cancer: a brief review of recent epidemiological evidence. Lung Cancer. 2004;45(Suppl 2):S3–9.PubMedCrossRef Sasco AJ, Secretan MB, Straif K. Tobacco smoking and cancer: a brief review of recent epidemiological evidence. Lung Cancer. 2004;45(Suppl 2):S3–9.PubMedCrossRef
152.
Zurück zum Zitat Vineis P, Alavanja M, Garte S. Dose–response relationship in tobacco-related cancers of bladder and lung: a biochemical interpretation. Int J Cancer. 2004;108:2–7.PubMedCrossRef Vineis P, Alavanja M, Garte S. Dose–response relationship in tobacco-related cancers of bladder and lung: a biochemical interpretation. Int J Cancer. 2004;108:2–7.PubMedCrossRef
153.
Zurück zum Zitat Shiels MS, Gibson T, Sampson J, Albanes D, Andreotti G, Beane Freeman L, et al. Cigarette smoking prior to first cancer and risk of second smoking-associated cancers among survivors of bladder, kidney, head and neck, and stage I lung cancers. J Clin Oncol. 2014;32:3989–95.PubMedPubMedCentralCrossRef Shiels MS, Gibson T, Sampson J, Albanes D, Andreotti G, Beane Freeman L, et al. Cigarette smoking prior to first cancer and risk of second smoking-associated cancers among survivors of bladder, kidney, head and neck, and stage I lung cancers. J Clin Oncol. 2014;32:3989–95.PubMedPubMedCentralCrossRef
154.
Zurück zum Zitat ’t Mannetje A, Kogevinas M, Chang-Claude J, Cordier S, González CA, Hours M, et al. Smoking as a confounder in case–control studies of occupational bladder cancer in women. Am J Ind Med. 1999;36:75–82.PubMedCrossRef ’t Mannetje A, Kogevinas M, Chang-Claude J, Cordier S, González CA, Hours M, et al. Smoking as a confounder in case–control studies of occupational bladder cancer in women. Am J Ind Med. 1999;36:75–82.PubMedCrossRef
155.
Zurück zum Zitat Akl EA, Gaddam S, Gunukula SK, Honeine R, Jaoude PA, Irani J. The effects of waterpipe tobacco smoking on health outcomes: a systematic review. Int J Epidemiol. 2010;39:834–57.PubMedCrossRef Akl EA, Gaddam S, Gunukula SK, Honeine R, Jaoude PA, Irani J. The effects of waterpipe tobacco smoking on health outcomes: a systematic review. Int J Epidemiol. 2010;39:834–57.PubMedCrossRef
156.
Zurück zum Zitat Rollison DE, Helzlsouer KJ, Pinney SM. Personal hair dye use and cancer: a systematic literature review and evaluation of exposure assessment in studies published since 1992. J Toxicol Environ Health B Crit Rev. 2006;9:413–39.PubMedCrossRef Rollison DE, Helzlsouer KJ, Pinney SM. Personal hair dye use and cancer: a systematic literature review and evaluation of exposure assessment in studies published since 1992. J Toxicol Environ Health B Crit Rev. 2006;9:413–39.PubMedCrossRef
157.
Zurück zum Zitat Bosetti C, Pira E, La Vecchia C. Bladder cancer risk in painters: a review of the epidemiological evidence, 1989–2004. Cancer Causes Control. 2005;16:997–1008.PubMedCrossRef Bosetti C, Pira E, La Vecchia C. Bladder cancer risk in painters: a review of the epidemiological evidence, 1989–2004. Cancer Causes Control. 2005;16:997–1008.PubMedCrossRef
158.
Zurück zum Zitat Guha N, Steenland NK, Merletti F, Altieri A, Cogliano V, Straif K. Bladder cancer risk in painters: a meta-analysis. Occup Environ Med. 2010;67:568–73.PubMedCrossRef Guha N, Steenland NK, Merletti F, Altieri A, Cogliano V, Straif K. Bladder cancer risk in painters: a meta-analysis. Occup Environ Med. 2010;67:568–73.PubMedCrossRef
159.
Zurück zum Zitat Bachand A, Mundt KA, Mundt DJ, Carlton LE. Meta-analyses of occupational exposure as a painter and lung and bladder cancer morbidity and mortality 1950–2008. Crit Rev Toxicol. 2010;40:101–25.PubMedCrossRef Bachand A, Mundt KA, Mundt DJ, Carlton LE. Meta-analyses of occupational exposure as a painter and lung and bladder cancer morbidity and mortality 1950–2008. Crit Rev Toxicol. 2010;40:101–25.PubMedCrossRef
160.
Zurück zum Zitat Takkouche B, Regueira-Méndez C, Montes-Martínez A. Risk of cancer among hairdressers and related workers: a meta-analysis. Int J Epidemiol. 2009;38:1512–31.PubMedCrossRef Takkouche B, Regueira-Méndez C, Montes-Martínez A. Risk of cancer among hairdressers and related workers: a meta-analysis. Int J Epidemiol. 2009;38:1512–31.PubMedCrossRef
161.
Zurück zum Zitat Harling M, Schablon A, Schedlbauer G, Dulon M, Nienhaus A. Bladder cancer among hairdressers: a meta-analysis. Occup Environ Med. 2010;67:351–8.PubMedPubMedCentralCrossRef Harling M, Schablon A, Schedlbauer G, Dulon M, Nienhaus A. Bladder cancer among hairdressers: a meta-analysis. Occup Environ Med. 2010;67:351–8.PubMedPubMedCentralCrossRef
162.
Zurück zum Zitat ’t Mannetje A, Pearce N. Bladder cancer risk in sales workers: artefact or cause for concern? Am J Ind Med. 2006;49:175–86.PubMedCrossRef ’t Mannetje A, Pearce N. Bladder cancer risk in sales workers: artefact or cause for concern? Am J Ind Med. 2006;49:175–86.PubMedCrossRef
163.
Zurück zum Zitat Boffetta P, Silverman DT. A meta-analysis of bladder cancer and diesel exhaust exposure. Epidemiology. 2001;12:125–30.PubMedCrossRef Boffetta P, Silverman DT. A meta-analysis of bladder cancer and diesel exhaust exposure. Epidemiology. 2001;12:125–30.PubMedCrossRef
164.
Zurück zum Zitat Manju L, George PS, Mathew A. Urinary bladder cancer risk among motor vehicle drivers: a meta-analysis of the evidence, 1977–2008. Asian Pac J Cancer Prev. 2009;10:287–94.PubMed Manju L, George PS, Mathew A. Urinary bladder cancer risk among motor vehicle drivers: a meta-analysis of the evidence, 1977–2008. Asian Pac J Cancer Prev. 2009;10:287–94.PubMed
165.
Zurück zum Zitat Acquavella J, Olsen G, Cole P, Ireland B, Kaneene J, Schuman S, et al. Cancer among farmers: a meta-analysis. Ann Epidemiol. 1998;8:64–74.PubMedCrossRef Acquavella J, Olsen G, Cole P, Ireland B, Kaneene J, Schuman S, et al. Cancer among farmers: a meta-analysis. Ann Epidemiol. 1998;8:64–74.PubMedCrossRef
167.
Zurück zum Zitat Mastrangelo G, Fedeli U, Fadda E, Milan G, Lange JH. Epidemiologic evidence of cancer risk in textile industry workers: a review and update. Toxicol Ind Health. 2002;18:171–81.PubMedCrossRef Mastrangelo G, Fedeli U, Fadda E, Milan G, Lange JH. Epidemiologic evidence of cancer risk in textile industry workers: a review and update. Toxicol Ind Health. 2002;18:171–81.PubMedCrossRef
168.
Zurück zum Zitat Tokumaru O, Haruki K, Bacal K, Katagiri T, Yamamoto T, Sakurai Y. Incidence of cancer among female flight attendants: a meta-analysis. J Travel Med. 2006;13:127–32.PubMedCrossRef Tokumaru O, Haruki K, Bacal K, Katagiri T, Yamamoto T, Sakurai Y. Incidence of cancer among female flight attendants: a meta-analysis. J Travel Med. 2006;13:127–32.PubMedCrossRef
169.
Zurück zum Zitat Buja A, Mastrangelo G, Perissinotto E, Grigoletto F, Frigo AC, Rausa G, et al. Cancer Incidence among female flight attendants: a meta-analysis of published data. J Women’s Heal. 2006;15:98–105.CrossRef Buja A, Mastrangelo G, Perissinotto E, Grigoletto F, Frigo AC, Rausa G, et al. Cancer Incidence among female flight attendants: a meta-analysis of published data. J Women’s Heal. 2006;15:98–105.CrossRef
170.
Zurück zum Zitat Wong O, Raabe GK. A critical review of cancer epidemiology in the petroleum industry, with a meta-analysis of a combined database of more than 350,000 workers. Regul Toxicol Pharmacol. 2000;32:78–98.PubMedCrossRef Wong O, Raabe GK. A critical review of cancer epidemiology in the petroleum industry, with a meta-analysis of a combined database of more than 350,000 workers. Regul Toxicol Pharmacol. 2000;32:78–98.PubMedCrossRef
171.
Zurück zum Zitat Baena AV, Allam MF, Díaz-Molina C, Del Castillo AS, Abdel-Rahman AG, Navajas RF-C. Urinary bladder cancer and the petroleum industry: a quantitative review. Eur J Cancer Prev. 2006;15:493–7.PubMedCrossRef Baena AV, Allam MF, Díaz-Molina C, Del Castillo AS, Abdel-Rahman AG, Navajas RF-C. Urinary bladder cancer and the petroleum industry: a quantitative review. Eur J Cancer Prev. 2006;15:493–7.PubMedCrossRef
172.
Zurück zum Zitat Greenberg RS, Mandel JS, Pastides H, Britton NL, Rudenko L, Starr TB. A meta-analysis of cohort studies describing mortality and cancer incidence among chemical workers in the United States and western Europe. Epidemiology. 2001;12:727–40.PubMedCrossRef Greenberg RS, Mandel JS, Pastides H, Britton NL, Rudenko L, Starr TB. A meta-analysis of cohort studies describing mortality and cancer incidence among chemical workers in the United States and western Europe. Epidemiology. 2001;12:727–40.PubMedCrossRef
173.
Zurück zum Zitat Vlaanderen J, Straif K, Ruder A, Blair A, Hansen J, Lynge E, et al. Tetrachloroethylene exposure and bladder cancer risk: a meta-analysis of dry-cleaning-worker studies. Environ Health Perspect. 2014;122:661–6.PubMedPubMedCentral Vlaanderen J, Straif K, Ruder A, Blair A, Hansen J, Lynge E, et al. Tetrachloroethylene exposure and bladder cancer risk: a meta-analysis of dry-cleaning-worker studies. Environ Health Perspect. 2014;122:661–6.PubMedPubMedCentral
174.
Zurück zum Zitat Fu H, Boffetta P. Cancer and occupational exposure to inorganic lead compounds: a meta-analysis of published data. Occup Environ Med. 1995;52:73–81.PubMedPubMedCentralCrossRef Fu H, Boffetta P. Cancer and occupational exposure to inorganic lead compounds: a meta-analysis of published data. Occup Environ Med. 1995;52:73–81.PubMedPubMedCentralCrossRef
175.
Zurück zum Zitat Cole P, Mandel JS, Collins JJ. Acrylonitrile and cancer: a review of the epidemiology. Regul Toxicol Pharmacol. 2008;52:342–51.PubMedCrossRef Cole P, Mandel JS, Collins JJ. Acrylonitrile and cancer: a review of the epidemiology. Regul Toxicol Pharmacol. 2008;52:342–51.PubMedCrossRef
176.
Zurück zum Zitat Collins JJ, Acquavella JF. Review and meta-analysis of studies of acrylonitrile workers. Scand J Work Environ Health. 1998;24(Suppl 2):71–80.PubMed Collins JJ, Acquavella JF. Review and meta-analysis of studies of acrylonitrile workers. Scand J Work Environ Health. 1998;24(Suppl 2):71–80.PubMed
177.
Zurück zum Zitat Bosetti C, Boffetta P, La Vecchia C. Occupational exposures to polycyclic aromatic hydrocarbons, and respiratory and urinary tract cancers: a quantitative review to 2005. Ann Oncol. 2007;18:431–46.PubMedCrossRef Bosetti C, Boffetta P, La Vecchia C. Occupational exposures to polycyclic aromatic hydrocarbons, and respiratory and urinary tract cancers: a quantitative review to 2005. Ann Oncol. 2007;18:431–46.PubMedCrossRef
178.
Zurück zum Zitat Boffetta P, Jourenkova N, Gustavsson P. Cancer risk from occupational and environmental exposure to polycyclic aromatic hydrocarbons. Cancer Causes Control. 1997;8:444–72.CrossRefPubMed Boffetta P, Jourenkova N, Gustavsson P. Cancer risk from occupational and environmental exposure to polycyclic aromatic hydrocarbons. Cancer Causes Control. 1997;8:444–72.CrossRefPubMed
179.
Zurück zum Zitat Rota M, Bosetti C, Boccia S, Boffetta P, La Vecchia C. Occupational exposures to polycyclic aromatic hydrocarbons and respiratory and urinary tract cancers: an updated systematic review and a meta-analysis to 2014. Arch Toxicol. 2014;88:1479–90.PubMedCrossRef Rota M, Bosetti C, Boccia S, Boffetta P, La Vecchia C. Occupational exposures to polycyclic aromatic hydrocarbons and respiratory and urinary tract cancers: an updated systematic review and a meta-analysis to 2014. Arch Toxicol. 2014;88:1479–90.PubMedCrossRef
180.
Zurück zum Zitat Calvert GM, Ward E, Schnorr TM, Fine LJ. Cancer risks among workers exposed to metalworking fluids: a systematic review. Am J Ind Med. 1998;33:282–92.PubMedCrossRef Calvert GM, Ward E, Schnorr TM, Fine LJ. Cancer risks among workers exposed to metalworking fluids: a systematic review. Am J Ind Med. 1998;33:282–92.PubMedCrossRef
181.
Zurück zum Zitat Mundt KA, Birk T, Burch MT. Critical review of the epidemiological literature on occupational exposure to perchloroethylene and cancer. Int Arch Occup Environ Health. 2003;76:473–91.PubMedCrossRef Mundt KA, Birk T, Burch MT. Critical review of the epidemiological literature on occupational exposure to perchloroethylene and cancer. Int Arch Occup Environ Health. 2003;76:473–91.PubMedCrossRef
182.
Zurück zum Zitat Goodman M, Morgan RW, Ray R, Malloy CD, Zhao K. Cancer in asbestos-exposed occupational cohorts: a meta-analysis. Cancer Causes Control. 1999;10:453–65.PubMedCrossRef Goodman M, Morgan RW, Ray R, Malloy CD, Zhao K. Cancer in asbestos-exposed occupational cohorts: a meta-analysis. Cancer Causes Control. 1999;10:453–65.PubMedCrossRef
183.
Zurück zum Zitat International Labour Office (ILO). International Standard Classification of Occupations. Revised Edition 1968. Geneva: International Labour Office (ILO); 1969. International Labour Office (ILO). International Standard Classification of Occupations. Revised Edition 1968. Geneva: International Labour Office (ILO); 1969.
184.
Zurück zum Zitat Statistical Office of the United Nations. International standard industrial classification of all economic activities. Statistical papers series M, number 4, revision 2. 1968. Statistical Office of the United Nations. International standard industrial classification of all economic activities. Statistical papers series M, number 4, revision 2. 1968.
Metadaten
Titel
Modifiable risk factors for the prevention of bladder cancer: a systematic review of meta-analyses
verfasst von
Abdulmohsen H. Al-Zalabani
Kelly F. J. Stewart
Anke Wesselius
Annemie M. W. J. Schols
Maurice P. Zeegers
Publikationsdatum
21.03.2016
Verlag
Springer Netherlands
Erschienen in
European Journal of Epidemiology / Ausgabe 9/2016
Print ISSN: 0393-2990
Elektronische ISSN: 1573-7284
DOI
https://doi.org/10.1007/s10654-016-0138-6

Weitere Artikel der Ausgabe 9/2016

European Journal of Epidemiology 9/2016 Zur Ausgabe