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Parity and bladder cancer risk: a dose-response meta-analysis

  • Yunjin Bai1,
  • Xiaoming Wang1,
  • Yubo Yang1,
  • Yin Tang1,
  • Jia Wang1 and
  • Ping Han1Email author
Contributed equally
BMC Cancer201717:31

https://doi.org/10.1186/s12885-016-3023-5

Received: 16 January 2016

Accepted: 20 December 2016

Published: 6 January 2017

Abstract

Background

Multiple studies have reported evidence of an inverse association between parity and bladder cancer risk. However, a comprehensive and quantitative assessment of this association has never been conducted. We conducted this study to clarify this issue.

Methods

Systematic search of PubMed and Embase was performed to identify all the studies. Studies were selected based on strict screening with inclusion and exclusion criteria. Summary relative risks (RR) with 95% confidence intervals (CI) were calculated by using a fixed-effect model, and the generalized least squares trend estimation was employed to compute study-specific RR and 95% CI per live birth increase. Heterogeneity and publication bias were also evaluated.

Results

Twelve studies (6,214 cases and 2,693,350 non-cases) were eligible in this meta-analysis. The pooled RR of bladder cancer for parous versus nulliparous women was 0.76 (95% CI: 0.70–0.82). Results were similar in the studies that adjusted for BMI(RR = 0.66; 95% CI: 0.53–0.81), cigarette smoking (RR = 0.67; 95% CI: 0.57–0.79), and age (RR = 0.77; 95% CI: 0.71–0.84). The dose-response meta-analysis showed a lower bladder cancer risk (RR = 0.95; 95% CI: 0.92–0.98) for each live birth increase in parous women. No evidence of publication bias or significant heterogeneity was detected in the above-mentioned analyses.

Conclusions

The finding from current meta-analysis suggest that parity may be related to decreased risk of bladder cancer.

Keywords

Parity Bladder cancer Meta-analysis Women’s health

Background

Bladder cancer (BC) is one of the most common genitourinary malignancies in the United States, with an estimated 76, 960 newly diagnosed cases and 16 390 deaths in 2016 [1]. Incidence rate of BC is notably gender-specific with men having a 3~4 fold greater risk than women for developing the disease [1]. Given the evidence from current knowledge, the gender disparity of incidence rate for BC cannot be completely explained by known risk factors, such as cigarette smoking and occupation [2].

Although the exact biological mechanisms for the gender disparity in BC development and progression are not well established, some studies have suggested that sex hormones and their receptors may contribute to this difference [35]. During pregnancy, changes in maternal hormones, as well as physical structure changes in the pelvic or lower abdominal region following childbirth, may lead to etiological changes that decrease BC risk. Till date, numerous observational studies [611] have investigated the roles of reproductive factors, such as age at menarche and menopause, parity, age at first birth, and number of children, in the development of BC, but results have been inconsistent, probably because of limited sample size included each individual study. Although published reviews and meta-analyses have focused on this topic [12, 13], up to now, a comprehensive and quantitative assessment of the relationship between parity number and BC risk has not been reported.

Therefore, we find it necessary to further assess the relationship between parity and BC risk by conducting a meta-analysis of current epidemiologic studies and providing a quantitative dose-response analysis.

Methods

This study protocol was approved by the institutional review board at the West China School of Medicine before initiation and don’t need ethical standard statement.

Literature search and eligibility criteria

We searched online databases MEDLINE and EMBASE for the studies assessing the relationship of parity and BC risk before Sep 2016, using the following terms with every possible combination considered: parity, pregnancy, reproductivity, fertility, bladder, genitourinary tract, cancer, carcinoma, tumor. We searched the references of all eligible publications to identify additional relevant publications. Studies were included if they met the following criteria: (1) the study had a prospective or case-control design; (2) the study evaluated the relationship between parity and BC risk; (3) data were provided or would allow the calculation of relative risk (RR) or odds ratio (OR) and a 95% confidence intervals (CI). Exclusion criteria were as follows: (1) was not involved with the associations between parity and BC risk; (2) non-human studies, reviews, and comments; (3) studies not reporting primary outcomes; (4) studies based on overlapping patients. When duplicate publications were identified or data in separate publications originated from the same cohort, we used the publication with the largest number of cases and the most applicable data.

Data extraction and quality assessment

Data were independently extracted from the included studies by two investigators (YJB and XMW), and disagreement was settled by discussion with the third investigator. The following data were extracted from each study: first author’ name, publication year, country of study, participant demographics, sample size, duration of follow-up or study period, parity number categories, corresponding OR/RR (with their 95% CIs) for each category, and variables adjusted for in the analysis.

The methodological quality assessment was conducted for each of the included studies using the Newcastle-Ottawa Scale quality assessment [14] on three broad perspectives: selection, comparability and exposure or outcome. Two investigators read each included study and scored them independently. Disagreements were resolved by consensus.

Statistical analysis

Given that bladder cancer is a rare disease, the OR was assumed to be the same as the RR and we therefore report all effect sizes as RR for simplicity. We calculated summary RRs and 95% CIs associated with parity and BC risk, if the study considered nulliparous as a reference. Between-study heterogeneity was evaluated with Q and I2 statistics [15]. For the Q-test, we used P < 0.10 as evidence of heterogeneity. An I2 score exceeding 50% is considered to indicate the presence of heterogeneity. The random effect model was used to provide summary estimations if there was heterogeneity, or else the fixed effect model was used. Heterogeneity was explored by stratified analysis. Publication bias was explored using Begg’s and Egger’s test [16, 17] and funnel plots. P < 0.05 indicated the existence of publication bias.

We carried out a dose-response meta-analysis using the method proposed by Greenland et al. [18] and Orsini et al. [19] to estimate study-specific slopes (linear trends) and 95% CIs from the log-RRs and CIs across the categories of parity number. This analysis requires the number of cases and controls for case-control studies or the number of cases and person-years for cohort studies, and the RR with 95% CI for at least three quantitative categories of parity number are presented. The value assigned to each category was the midpoint of the upper and lower boundaries and was adjusted for half range of the neighborhood categories when categories were open-ended. Random-effects model was applied in our study. This was done by modeling parity number using restricted cubic splines with three knots at percentiles 5, 50, and 95% of the distribution. A P value for nonlinearity was computed by testing the null hypothesis that the coefficient of the second spline was equal to zero. Statistical analyses were performed with Stata version 12.0 software (Stata Corp, College Station, TX).

Results

Study characteristics and quality assessment

The article selection process is shown in Fig. 1. Thirteen articles [613, 2024] met the selection criteria. Two studies reported data on the same cohort [9, 22] and we included the more recently one which reported the largest number of cases [22]. Thus, 12 publications were included in this meta-analysis [68, 1013, 2024], and their characteristics are presented in Table 1. These studies included a total of 6,214 cases and 2,693,350 non-cases and were published from 1992 to 2013. Among these studies, one study reported three separate outcomes: the Los Angeles Bladder Cancer Study, the Shanghai Bladder Cancer Study, and the California Teachers Study [13]. Thus, the present study used seven outcomes from case-control studies and seven outcomes from cohort studies to produce a meta-analysis. Of the included studies, 13 were conducted in Europe, nine in America and one in China. All studies included met quality criteria ranging from 5 to 7 stars.
Fig. 1

Flow diagram of the study selection process

Table 1

Characteristics of eligible studies included in this meta-analysis of parity and bladder cancer risk

Author, year

Design, study name

Country, study period

Study qualitya

Age

Cases; participants/controls

Parity

OR (95% CI)

Adjustment factors

Cantor et al. 1992 [20]

Case-control study

USA, 1986–1989

5

40–85

315; 821

1

Reference

Not reported

      

2

1.4 (0.8–2.4)

      

3

1.6 (0.9–2.9)

      

4

0.9 (0.5–1.8)

      

5+

1.5 (0.8–2.7)

La Vecchia et al. 1993 [21]

Case-control study

Italy, 1983–1992

6

Case: blow 70; Control: 58 (median)

68; 5619

0

Reference

Age, education, parity, number of abortions, oral contraceptive and other female hormone use

      

1

1.2

      

2

1.0

      

3

0.8

      

≥4

0.7

Pelucchi et al. 2002 [10]

Case-control study

Italy, 1985–1992

6

Case: 30–79 Control: 26–79

110; 289

0–1

Reference

Age, study center, education, BMI, cigarette smoking, and coffee and alcohol consumption

      

2–3

0.83 (0.47–1.45)

      

≥4

0.88(0.41–1.90)

Cantwell et al. 2006 [8]

Cohort study

USA, 1980–1998

7

Case: 55.4 ± 8.8 Participants: 70.6 ± 8.4,

167; 54308

0

Reference

Age, calendar year and smoking status (never, former or current).

      

1

0.65 (0.36–1.18)

      

2

0.96 (0,61–1,。50)

      

3

0.82 (0.5–1.34)

      

>4

0.75 (0.45–1.25)

McGrath et al. 2006 [11]

Cohort study, US Nurses’ Health Study

USA, 1976–2002

7

30–55

336; 116598

0

Reference

Age (months), time period (2-year questionnaire period), smoking status (never, former, current) and pack-years of smoking (continuous), and body mass index

      

1–2

0.85 (0.56–1.28)

      

3–4

0.70 (0.47–1.05)

      

≥4

0.84 (0.54–1.32)

Prizment et al. 2006 [22]

Cohort study, The Iowa Women’s Health Study

USA, 1986–2003

7

55–69

192; 37459

0

Reference

Age, smoking status and pack-years

      

1–2

0.81 (0.50–1.32)

      

3–4

0.79 (0.48–1.27)

      

≥5

0.79 (0.46–1.37)

Huang et al. 2009 [7]

Case-control study

Spanish, 1998–2001

6

Median: case 67.4

152; 166

0

Reference

Age, smoking status, and high-risk occupation

    

Control:67.8

 

≥1

0.43 (0.2–0.9)

Davis-Dao et al. 2011 [13]

 

USA and China,

6

LAS:25–64;

LAS:349/349

LA:1

LA: Reference

LASBCS: smoking status in the reference year (current, former, never), pack-years of smoking, and BMI; CTS: race/ethnicity, smoking status and BMI.

 

Los Angeles Bladder Cancer Study (LAS): Case-control study;

Los Angeles: 1987–1996;

 

SHS:25–74;

SHS: 131/138

2

0.41 (0.98–0.87)

  

CTS: not reported

CTS: 196/120857

3

0.63 (0.29–1.34)

     

≥4

0.70 (0.35–1.39)

 

Shanghai Bladder Cancer Study (SHS): Case-control study

Shanghai:1995–1998;

   

SH: 1

SH: reference

     

2

0.63 (0.23–1.74)

     

3

0.47 (0.16–1.33)

 

California Teachers Study(CTS): Cohort study

CTS:1995–2005

   

≥4

0.56 (0.21–1.48)

     

CTS:1

CTS: reference

      

2

1.14 (0.71–1.86)

      

3

0.73 (0.42–1.27)

      

≥4

1.06 (0.61–1.87)

Dietrich et al. 2011 [12]

Case-control study

USA, 1994–2001; 1993

6

25–74

207/403

0

Reference

Age and smoking status

  

July; 1995–1997

   

1–2

0.67 (0.36–1.24)

      

3–4

0.75 (0.40–1.39)

      

≥5

0.74 (0.35–1.57)

Daugherty et al. 2013 [23]

Cohort study, NIH-AARP Diet and Health Study

USA, 1995–2006

7

50–71

651/201492

0

Reference

Age

      

1

0.78 (0.58–1.07)

      

2

0.72 (0.56–0.92)

      

3–4

0.78 (0.62–0.98)

      

5+

0.73 (0.54–0.98)

Kabat et al. 2013 [24]

Cohort study, Women’s Health Initiative

USA, 1993–1998

6

50–79

480/145048

0

Reference

Age, education, pack-years, alcohol intake, parity, oral contraceptive use (ever, never)

      

1–2

0.71 (0.53–0.96)

      

3–4

0.84 (0.63–1.12)

      

≥5

0.72 (0.51–1.03)

Weibull et al. 2013 [6]

Cohort study

Sweden, 1964–2009, Median follow-up time:16.6 years

7

40~

2860/2009811

1

Reference

Age, highest educational level, and chronic obstructive lung disease.

      

2

0.85 (0.77–0.95)

      

≥3

0.76 (0.68–0.86)

aUsing the Newcastle-Ottawa Scale

Ever versus never parity

All included studies in present study investigated the association between ever parity and BC risk. The summary multivariable-adjusted RR of BC for ever versus nulliparous was 0.76 (95% CI, 0.70–0.82), without heterogeneity (I2 = 0%, p = 0.795, Fig. 2), indicating an inverse association between parity and BC risk. For women who have never smoked, the summary RR of BC for ever versus nulliparous was 0.47 (95% CI, 0.35–0.63), without heterogeneity (I2 = 0%, p = 0.562). For women who have ever smoked, the summary RR was 0.90 (95% CI, 0.67–1.21) for ever versus nulliparous, without heterogeneity (I2 = 0%, p = 0.531).
Fig. 2

Forest plot (fixed-effects model) of ever parity and bladder cancer risk

Differences with parity number

Six cohort and six case-control studies investigated possible association between parity and BC risk. The results of the effects of different parity number on BC risk are presented in Table 2. To clarify the effects, we divided the parity number into three groups. The first group (1–2 births) contained seven reports, compared with nulliparous,, the pooled RR of BC associated with giving birth to two children was 0.82 (95% CI 0.71–0.94) with I2 = 17.7% (P = 0.295). The second group (3–4 births) contained seven reports, compared with nulliparous, the overall RR of BC was 0.79 (95% CI 0.68–0.91) with I2 = 0% (P = 0.997). The third group (≥5 births) contained six reports, compared with nulliparous, the overall RR of BC was 0.76 (95% CI 0.66–0.88) with I2 = 0% (P = 0.994).
Table 2

Summary risk estimates of the association between parity and bladder cancer

 

No. of reports

RR (95% CI)

I2 (%)

P value

Overall

13

0.76 (0.70–0.82)

0

0.795

Number of parity

 1 ~ 2 vs. 0

7

0.82 (0.71–0.94)

17.7

0.295

 3 ~ 4 vs. 0

7

0.79 (0.68–0.91)

0

0.997

  ≥ 5 vs. 0

6

0.76 (0.66–0.88)

0

0.994

Subgroup analysis

 Study design

  Cohort study

6

0.77 (0.71–0.84)

0

0.802

  Case-control study

7

0.71 (0.60–0.83)

0

0.598

 Number of cases

   < 250

7

0.68 (0.56–0.81)

0

0.673

   > 250

6

0.78 (0.71–0.84)

0

0.841

 Location

  USA

9

0.72 (0.65–0.81)

0

0.989

  Others

4

0.79 (0.71–0.87)

39.7

0.174

 Smoking

  Never smoking

5

0.47 (0.35–0.63)

0

0.562

  Ever smoking

4

0.90 (0.67–1.21)

0

0.531

 Adjustment for smoking

  Yes

8

0.67 (0.57–0.79)

0

0.815

  No

5

0.79 (0.72–0.86)

0

0.882

 Adjustment for age

  Yes

9

0.77 (0.71–0.84)

0

0.850

  No

4

0.65 (0.52–0.81)

0

0.684

 Adjustment for BMI

  Yes

5

0.66 (0.53–0.81)

0

0.469

  No

8

0.76 (0.70–0.82)

0

0.952

Dose-response meta-analysis

Dose-response from nine studies [6, 8, 1113, 2023] showed a decreased in BC risk of 0.95 (95% CI: 0.92–0.98) per live birth increase, without heterogeneity (I2 = 12.79%, P = 0.7832). Compared with nulliparous individuals, the pooled RRs (95% CI) of BC were 0.84 (0.76–0.94), 0.76 (0.67–0.87), 0.74 (0.65–0.85), 0.75 (0.66–0.85), and 0.76 (0.65–0.88) for 1, 2, 3, 4, and 5 live births, respectively (Fig. 3).
Fig. 3

Nonlinear dose-response relationship between parity and bladder cancer risk

Publication bias

No evidence of a significant publication bias was observed in our analyses as assessed using the Egger’s test or Begg’s test and no asymmetry was seen in the funnel plots of included studies.

Subgroup analyses

To avoid the influence of cigarette smoking, we evaluated the influence of smoking status by adjustment in the eight reports that considered smoking. However, when data were stratified by adjustment for smoking, we did not find a significant difference between summary RRs that were adjusted and those that were not adjusted for smoking (Table 2). Moreover, significant inverse associations were persisted after the subgroup analyses stratified by whether the study included adjustment for specific potential confounders, such as age, Body Mass Index (BMI), type of control subjects or others potential confounders (Table 2). An additional file shows this in more detail (see Additional file 1).

Discussion

Numerous epidemiological studies have focused on BC risk factors in order to explain the gender disparity in BC incidence, while there is also a great interest in identifying factors that affect the risk of BC among women. Although previous studies have reported on the associations between parity and BC, to the best of our knowledge, no other earlier studies have clearly documented a dose-response pattern between parity number and BC risk. In present study, we conducted a dose-response meta-analysis to characterize the association between parity and BC risk. Findings from the present study indicated that parous was significantly inversely associated with BC risk compared with nulliparous, especially for non-smokers. Overall, the risk of BC decreased by 24% for women who had given birth and 53% for those who had never smoked and were ever parous.

Although the exact mechanisms underlying this inverse association between parity and BC risk are not completely established, several potential mechanisms have been proposed. First, during pregnancy, estrogen and progesterone levels increase drastically and induce substantial alterations to the structure, function, and histology of the bladder [25], possibly affecting the development and progression of BC. Both estrogen and progesterone receptors are found in bladder tissues suggesting that endocrine regulation could directly influence BC development [26]. Shen et al. [27] found that antiestrogens have an inhibitory effect on the growth of BC cells in vitro, indicating that estrogens may increase the development and growth of bladder malignancies. Some research has reported that progesterone suppresses the activity of the estrogen receptor during pregnancy [28]. Therefore, estrogen and progesterone have an antagonistic effects on human cells. The substantial increased in their levels during pregnancy may responsible for the decreased risk of BC for women. Moreover, a hormone-related protective effect based on the prity number may mirror the lifetime period of lactation and prolonged oxytocin inhibition of steroid hormones [6].

Second, smoking habits may have influenced the incidence of BC in women with parity. It is well known that prenatal cigarette smoking exposure may cause detrimental effects on reproductive health [29]. Therefore, most smokers who prepare for pregnancy are more likely to quit smoking. Thus, compared with nulliparous female smokers, parous smokers who quit smoking may have a shorter smoking exposure history and reduction of pack years, and this may affect their BC risk. In addition, cumulative effect of abandon smoking following multiple pregnancies may also associate to decrease the subsequent risk of BC. The findings of our study suggest that the negative correlation between parity and BC appears more remarkable among women who were never exposed to cigarettes, with these parous women experiencing at least a 53% decreased risk of BC compared with nulliparous women. However, such a dramatic risk reduction was not apparent among smokers. The reasons for this results of subgroup analysis may be that the effect of smoking on BC is so huge that for the development of the disease minor influence factors such as parity are less relevant. In case of never smokers, these minor influence factors play indeed a role.

Third, structural changes in the pelvic organs and pelvic floor organization following pregnancy may induce a decreased risk for BC in parous women. Childbirth is an established risk factor for lower urinary tract dysfunction, such as increased urinary frequency, stress incontinence, and overactive bladder [30], but the possible relationship with BC remains unclear. It is well known that BC risk is related to the contact time of the urothelium with carcinogens in urine. Some study reported that increased water intake and urination frequency may lessen contact time of urinary carcinogens with urothelium of the bladder, thus, diminish the bladder cancer risk [31, 32]. Zhang et al. [31] found that increasing urination frequency during daytime was associated with decreased risk of bladder cancer. Silverman et al. [32] suggested that nocturia may be a powerful factor in reducing BC risk. Based on the results of above studies, we can be reasonable to assume that lower urinary tract dysfunction after childbirth has a protective effect on BC risk, and this may be associated with shorter duration of exposure to urine carcinogens in the bladder. Further research should verify this hypothesis.

Meta-analyses of observational studies are prone to confounding, selection, and information bias as the included observational studies and can present particular challenges that may distort the results. However, our study has some strengths. First, we searched 2 electronic databases, which ensured a broad scope, and we included seven cohorts and seven case-control studies that involved a total of 6,214 cases and 2,693,350 non-cases. This large sample size should have provided sufficient statistical power to detect this potential relationship. Second, to control misclassification, we conducted a dose-response meta-analysis. This is the most comprehensive meta-analysis evaluating the associations between parity and BC. Third, no publication biases were detected in present study and outcome may be unlikely to remain unreported as studies with complex assessment of exposure.

Conclusions

This current dose-response meta-analysis indicates that women with parity have an inversely associated BC risk compared with nulliparous women. The exact mechanism underlying this protective effect requires further investigation.

Abbreviations

BC: 

Bladder cancer

BMI: 

Body mass index

CI: 

Confidence interval

OR: 

Odds ratio

RR: 

Relative risk

Declarations

Acknowledgements

Thanks to the help of the members of the urology department in West China Hospital of Sichuan University, especially QW, CXP and JHL.

Funding

This work was collectively supported by grant (National Natural Science Foundation of China (No. 81270841)), and Science & Technology Pillar Program from Science & Technology Department of Sichuan Province (2013SZ0034). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Availability of data and materials

All data generated or analysed during this study are included in this published article.

Authors’ contributions

Conceived and designed the experiments: PH. Analyzed the data: JYB and XMW. Contributed reagents/materials/analysis YBY, YT and JW. Wrote the manuscript: JYB, XMW and JW. All authors have read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Urology, Institute of Urology, West China Hospital, Sichuan University

References

  1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66:7–30.View ArticlePubMedGoogle Scholar
  2. Hartge P, Harvey EB, Linehan WM, Silverman DT, Sullivan JW, Hoover RN, Fraumeni Jr JF. Unexplained excess risk of bladder cancer in men. J Natl Cancer Inst. 1990;82:1636–40.View ArticlePubMedGoogle Scholar
  3. Bolenz C, Lotan Y, Ashfaq R, Shariat SF. Estrogen and progesterone hormonal receptor expression in urothelial carcinoma of the bladder. Eur Urol. 2009;56:1093–5.View ArticlePubMedGoogle Scholar
  4. Lucca I, Fajkovic H, Klatte T. Sex steroids and gender differences in nonmuscle invasive bladder cancer. Curr Opin Urol. 2014;24:500–5.View ArticlePubMedGoogle Scholar
  5. Gakis G, Stenzl A. Gender-specific differences in muscle-invasive bladder cancer: the concept of sex steroid sensitivity. World J Urol. 2013;31:1059–64.View ArticlePubMedGoogle Scholar
  6. Weibull CE, Eloranta S, Altman D, Johansson AL, Lambe M. Childbearing and the risk of bladder cancer: a nationwide population-based cohort study. Eur Urol. 2013;63:733–8.View ArticlePubMedGoogle Scholar
  7. Huang AT, Kogevinas M, Silverman DT, Malats N, Rothman N, Tardón A, Serra C, García-Closas R, Carrato A, Cantor KP. Bladder cancer and reproductive factors among women in Spain. Cancer Causes Control. 2009;20:1907–13.View ArticlePubMedPubMed CentralGoogle Scholar
  8. Cantwell MM, Lacey Jr JV, Schairer C, Schatzkin A, Michaud DS. Reproductive factors, exogenous hormone use and bladder cancer risk in a prospective study. Int J Cancer. 2006;119:2398–401.View ArticlePubMedGoogle Scholar
  9. Tripathi A, Folsom AR, Anderson KE, Iowa Women’s Health Study. Risk factors for urinary bladder carcinoma in postmenopausal women. The Iowa Women’s Health Study. Cancer. 2002;95:2316–23.View ArticlePubMedGoogle Scholar
  10. Pelucchi C, La Vecchia C, Negri E, Dal Maso L, Franceschi S. Smoking and other risk factors for bladder cancer in women. Prev Med. 2002;35:114–20.View ArticlePubMedGoogle Scholar
  11. McGrath M, Michaud DS, De Vivo I. Hormonal and reproductive factors and the risk of bladder cancer in women. Am J Epidemiol. 2006;163:236–44.View ArticlePubMedGoogle Scholar
  12. Dietrich K, Demidenko E, Schned A, Zens MS, Heaney J, Karagas MR. Parity, early menopause and the incidence of bladder cancer in women: a case-control study and meta-analysis. Eur J Cancer. 2011;47:592–9.View ArticlePubMedGoogle Scholar
  13. Davis-Dao CA, Henderson KD, Sullivan-Halley J, Ma H, West D, Xiang YB, Gago-Dominguez M, Stern MC, Castelao JE, Conti DV, Pike MC, Bernstein L, Cortessis VK. Lower risk in parous women suggests that hormonal factors are important in bladder cancer etiology. Cancer Epidemiol Biomarkers Prev. 2011;20:1156–70.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25:603–5.View ArticlePubMedGoogle Scholar
  15. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–60.View ArticlePubMedPubMed CentralGoogle Scholar
  16. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50:1088–101.View ArticlePubMedGoogle Scholar
  17. Egger M, Davey SG, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629–34.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Greenland S, Longnecker MP. Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol. 1992;135:1301–9.PubMedGoogle Scholar
  19. Orsini N, Bellocco R, Greenland S. Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software. Am J Epidemiol. 2012;175:66–73.View ArticlePubMedGoogle Scholar
  20. Cantor KP, Lynch CF, Johnson D. Bladder cancer, parity, and age at first birth. Cancer Causes Control. 1992;3:57–62.View ArticlePubMedGoogle Scholar
  21. La Vecchia C, Negri E, Franceschi S, Parazzini F. Long-term impact of reproductive factors on cancer risk. Int J Cancer. 1993;53:215–9.View ArticlePubMedGoogle Scholar
  22. Prizment AE, Anderson KE, Harlow BL, Folsom AR. Reproductive risk factors for incident bladder cancer: Iowa Women’s Health Study. Int J Cancer. 2006;120:1093–8.View ArticleGoogle Scholar
  23. Daugherty SE, Lacey Jr JV, Pfeiffer RM, Park Y, Hoover RN, Silverman DT. Reproductive factors and menopausal hormone therapy and bladder cancer risk in the NIH-AARP Diet and Health Study. Int J Cancer. 2013;133:462–72.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Kabat GC, Kim MY, Luo J, Hou L, Cetnar J, Wactawski-Wende J, Rohan TE. Menstrual and reproductive factors and exogenous hormone use and risk of transitional cell bladder cancer in postmenopausal women. Eur J Cancer Prev. 2013;22:409–16.View ArticlePubMedGoogle Scholar
  25. Rodrìguez LV, Wang B, Shortliffe LM. Structural changes in the bladder walls of pregnant and hormone-treated rats: correlation with bladder dynamics. BJU Int. 2004;94:1366–72.View ArticlePubMedGoogle Scholar
  26. Blakeman PJ, Hilton P, Bulmer JN. Cellular proliferation in the female lower urinary tract with reference to oestrogen status. BJOG. 2001;108:813–6.PubMedGoogle Scholar
  27. Shen SS, Smith CL, Hsieh JT, Yu J, Kim IY, Jian W, Sonpavde G, Ayala GE, Younes M, Lerner SP. Expression of estrogen receptors-alpha and -beta in bladder cancer cell lines and human bladder tumor tissue. Cancer. 2006;106:2610–6.View ArticlePubMedGoogle Scholar
  28. Batra SC, Iosif CS. Progesterone receptors in the female lower urinary tract. J Urol. 1987;138:1301–4.PubMedGoogle Scholar
  29. Håkonsen LB, Ernst A, Ramlau-Hansen CH. Maternal cigarette smoking during pregnancy and reproductive health in children: a review of epidemiological studies. Asian J Androl. 2014;16:39–49.View ArticlePubMedGoogle Scholar
  30. Chaliha C, Stanton SL. Urological problems in pregnancy. BJU Int. 2002;89:469–76.View ArticlePubMedGoogle Scholar
  31. Zhang W, Xiang YB, Fang RR, Cheng JR, Yuan JM, Gao YT. Total fluid intake, urination frequency and risk of bladder cancer: a population-based case-control study in urban Shanghai. Zhonghua Liu Xing Bing Xue Za Zhi. 2010;31:1120–4.PubMedGoogle Scholar
  32. Silverman DT, Alguacil J, Rothman N, Real FX, Garcia-Closas M, Cantor KP, Malats N, Tardon A, Serra C, Garcia-Closas R, Carrato A, Lloreta J, Samanic C, Dosemeci M, Kogevinas M. Does increased urination frequency protect against bladder cancer? Int J Cancer. 2008;123:1644–8.View ArticlePubMedGoogle Scholar

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© The Author(s). 2017