Literature DB >> 22158326

15. Cancers attributable to reproductive factors in the UK in 2010.

D M Parkin1.   

Abstract

Entities:  

Mesh:

Year:  2011        PMID: 22158326      PMCID: PMC3252053          DOI: 10.1038/bjc.2011.488

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


× No keyword cloud information.
Reproductive factors influence the risk of cancers of the female genital tract (uterus and ovary) and breast. The following reproductive factors are important in this respect: age at menarche; age at first birth; parity; age at menopause; and duration of breastfeeding. The effects of exogenous hormones are described in Section 10. Age at menarche Early age at menarche has been consistently associated with an increased risk of breast and endometrial cancer (Pike ). Relative risk (RR) for premenopausal breast cancer is reduced by an estimated 7% for each year that menarche is delayed after age 12 years, and by 3% for post-menopausal breast cancer (Clavel-Chapelon, 2002). The effect on risk is through prolongation of the period with relatively high exposure to endogenous oestrogen. Age at first birth The younger the woman is when she begins childbearing, the lower her risk of breast cancer (Kelsey ). The RR of developing breast cancer increases by 3% for each year of delay (Collaborative Group, 2002). Parity Increasing parity reduces the risk of breast, endometrial and ovarian cancers (Pike ). The higher the number of full-term pregnancies, the greater the protection. Compared with nulliparous women, a woman who has at least one full-term pregnancy reduces her risk of breast cancer by around 25% (Layde ; Ewertz ) and women with five or more children experience a 50% reduction in risk (Kelsey ). For endometrial cancer, risk is reduced by 30% for a woman’s first birth and by 25% for each successive birth, and later maternal age at last birth has also been shown to reduce the risk (Pike ). For ovarian cancer, risk in women with four pregnancies is only 40% that in nulliparous women (Ness ). However, increasing parity increases the risk of cancer of the cervix, independently of any increase in the prevalence of infection with HPV (Munoz ). Age at menopause Late menopause increases the risk of breast cancer and endometrial cancer (Pike ). For breast cancer, risk is doubled for a woman with menopause at 55 years compared with less than 45 years (Kelsey ). For each year that the menopause is delayed, there is an approximate 3% increase in breast cancer risk (Collaborative Group, 1997). Postmenopausal women have a lower risk of breast cancer compared with premenopausal women of the same age, both for natural menopause and for menopause induced through surgery (Collaborative Group, 1997). Breastfeeding The role of breastfeeding as a protective factor against the later development of breast cancer has been long suspected (Lane-Claypon, 1926). More recently, this association has been confirmed and the magnitude of the effect estimated as a decrease in risk of 4.3% for every 12 months of breastfeeding (Collaborative Group on Hormonal Factors in Breast Cancer, 2002). For ovarian cancer, the issue is less clear. An early collaborative analysis of case–control studies found a reduced risk in parous women who had ever breastfed compared with those who had never done so (Whittemore ). Subsequent work suggested that only serous tumours may be so influenced (Jordan , 2008). A recent analysis of two US cohort studies (Danforth ) suggests that each month of breastfeeding reduces the RR by 2% (RR=0.98 per month, 95% CI 0.97–1.00). Although a woman's reproductive behaviour can influence the risk of cancers of the uterus, ovary and breast, most of the important aspects discussed above are not sensibly considered as targets for preventive interventions. In this section, therefore, only the cancers attributable to sub-optimal levels of breastfeeding are evaluated.

Methods

Breastfeeding of infants in Britain is not very common, and is generally not prolonged for more than a few weeks. Surveys of infant feeding in the UK, at 5-yearly intervals since 1975, have been carried out by the Department of Health. The most recent survey (the seventh) was in 2005 (Bolling ). Table 1 shows the results of these surveys.
Table 1

Percentage of women breastfeeding at given intervals post partum (Great Britain)

  % Women breastfeeding, by year of survey
Interval post partum 1980 1985 1990 1995 2000 2005
Birth656362666976
1 Week 54 52 51 565563
2 Weeks 51 49 48 535260
6 Weeks 41 39 39 424248
4 Months 27 27 26 272834
6 Months 21 20 20 212125
8 Months 15 14 14 1516 21
9 Months 14 13 13 141318

Values in italics have been interpolated.

The values in italics have been interpolated. This seems relatively secure, as the decline in breastfeeding prevalence with time since birth in women who do actually commence seems to be relatively constant (Figure 1).
Figure 1

Percent of women continuing breastfeeding, by time since birth.

There is no generally accepted target for breastfeeding. The Global Strategy on Diet, Physical Activity and Health of the World Health Organisation (WHO, 2004) includes a recommendation to ‘promote and support exclusive breastfeeding for the first six months of life and promote programmes to ensure optimal feeding for all infants and young children’. Therefore, we have taken as the optimum breastfeeding of all live-born children for six months, with no change to the current pattern after this time. Currently, some 18% of women are breastfeeding to 9 months of age (Table 1). Table 2 gives information on the birth experience of women in England and Wales in 2008, the most recent year available (Office for National Statistics, 2009).
Table 2

Natality of women in England and Wales in 2008, by age/birth cohort

Age (years) Central birth year Average number of live-born children Average age when 50% children had been born Average year when 50% children had been born
0–420060
5–920010
10–1419960
15–1919910.04132004
20–2419860.34192003
25–2919810.80232001
30–3419761.34261999
35–3919711.75261996
40–4419661.90261991
45–4919611.96271985
50–5419562.02261980
55–5919512.04251974
60–6419462.19251968
65–6919412.34251964
70–7419362.40261960
75–7919312.35271956
80–8419262.12271951
⩾8519212.00271946
Table 3 shows the estimated duration of breastfeeding (based on the data of Table 1).
Table 3

Median and mean duration of breast feeding (Great Britain)

  Duration of breastfeeding (months) by year of survey
Average 1980 1985 1990 1995 2000 2005
Median0.600.480.380.840.711.46
Mean2.842.752.712.892.903.50
Mean if all ⩾6 monthsa6.786.756.746.796.787.02

Mean if all women could breastfeed their children for 6 months (so prevalence at 6 months is 100%).

With a change in risk for each month of breastfeeding of −0.366% for breast cancer and −2.0% for ovarian cancer (Collaborative Group on Hormonal Factors in Breast Cancer, 2002; Danforth ), the actual protection provided by the breastfeeding practices of each generation of women can be estimated (column 1 of Table 4). The breastfeeding practices from Table 1 are assumed to apply to the year in which 50% of the children in a given age group in 2008 would have been born. Since there are no data on breastfeeding practices prior to 1980, the duration of having been breastfed for women in the age groups ⩾55–59 are taken to be the same as in 1980.Table 3 also shows the estimated mean duration of breastfeeding if all women could breastfeed their children for 6 months (so that prevalence at 6 months is 100%), after which the values in Table 1 continue to pertain.
Table 4

Effect of breastfeeding on women's risk of breast and ovarian cancer, UK 2008

  Breast cancer
Ovarian cancer
  1 2 3 4 1 2 3 4
Age (years) Estimated individual decrease in risk Target decrease in risk a Excess risk PAF (%) Estimated individual decrease in risk Target decrease in risk a Excess risk PAF (%)
0–400
5–900
10–1400
15–190.00050.00100.0010.10.00260.00520.0030.3
20–240.00430.00860.0040.40.02190.04430.0222.3
25–290.00840.01960.0111.10.04290.10100.0586.1
30–340.01400.03280.0191.90.07180.16910.09710.5
35–390.01830.04290.0252.50.09350.22120.12814.1
40–440.01860.04630.0282.80.09510.23870.14415.9
45–490.01950.04780.0282.90.09970.24660.14716.3
50–540.02070.04950.0292.90.10600.25500.14916.7
55–590.02090.05000.0293.00.10710.25750.15016.8
60–640.02250.05360.0313.20.11490.27640.16118.2
65–690.02400.05730.0333.40.12280.29530.17319.7
70v740.02460.05880.0343.50.12600.30290.17720.2
75–790.02410.05760.0333.40.12330.29660.17319.8
80–840.02170.05190.0303.10.11130.26760.15617.6
⩾850.02050.04900.0282.90.10500.25240.14716.5

Abbreviation: PAF=population-attributable fraction.

If all had breastfed for a minimum of 6 months.

Results

Column 1 of Table 4 shows the decrease in risk of breast and ovarian cancer due to breastfeeding, of women in the UK, by age group, in 2008, and column 2 the decrease in risk if all had been breastfed for a minimum of 6 months. Column 3 shows the excess risk of women in 2008, due to their breastfeeding practice being short of target, and column 4 the population-attributable fraction of breast and ovarian cancer cases by age. In Table 5, we assume that the RR estimated for 2008 is pertinent for 2010, and show the actual numbers of cancer cases that would be attributable to breastfeeding practices not reaching the optimum level.
Table 5

Cases of breast and ovarian cancer estimated to be due to sub-optimal breast feeding, UK 2010

  Breast
Ovary
Age (years) Relative risk Observed cases Excess attributable cases PAF (%) Relative risk Observed cases Excess attributable cases PAF (%)
0–4120120
5–9100142
10–14100163
15–191.0005400.11.00262300.3
20–241.00443200.41.02345712.3
25–291.011416721.11.06469056.1
30–341.0194548101.91.11711031110.5
35–391.02581265322.51.16391602314.1
40–441.02912593732.81.18852784415.9
45–491.029842361232.91.19504287016.3
50–541.030348101412.91.19994988316.7
55–591.030655821663.01.202662310516.8
60–641.032964592063.21.223288316118.2
65–691.035364032193.41.244885216819.7
70–741.036343321523.51.253882816820.2
75–791.035540581393.41.246373414519.8
80–841.031835261093.11.213461610817.6
⩾851.029943671272.91.197363510516.5
All ages 48 38514983.1 6820120117.6

Abbreviation: PAF=population-attributable fraction.

In total 2699 cancer cases projected to occur in 2010 (1498 breast cancers, 1201 ovarian cancers) would have been avoided if breastfeeding practice had been at the theoretical ‘optimum’. This represents 1.7% of cancers in women and 0.9% of all cancer cases in 2010.

Discussion

Though it may be desirable, from the point of view of cancer prevention, to have multiple pregnancies commencing at a young age, there are equally, or more, persuasive reasons to avoid such a lifestyle. It makes no sense, therefore, to prescribe an ideal fertility pattern, against which the number of cancers attributable to a less optimum one can be evaluated. In the IARC calculation of avoidable cancers in France (IARC, 2007), the fertility pattern of 1980 was taken as an ideal against which the excess cases resulting from fertility in 2000 were calculated, although the rationale for this was not explained. The origin of the Doll and Peto (2003) estimate of 15% of UK cancer deaths being attributable to ‘reproduction’ (and other factors related to the secretion of reproductive hormones) is obscure; the methodology is said to be the same as in their 1981 monograph (Doll and Peto, 1981), although this considers some 46% of the deaths due to cancers of the breast, ovary and uterus (corpus and cervix) as attributable to reproductive and sexual factors, and these cancers are responsible for only 8% of cancer deaths in UK in 2005. It is reasonable, however, to advocate breastfeeding for a variety of reasons, of which the benefit of cancer protection is one (http://www.breastfeeding.nhs.uk/en/fe/page.asp?n1=2). The ‘optimum’ levels for breastfeeding against which attributable fractions of breast and ovarian cancer have been evaluated are rather artificial, in that it would be impossible for all women to breastfeed their infant for 6 months. In the United States, for example, the US Department of Health and Human Services (2005) Healthy People 2010 objectives for breastfeeding initiation and duration were to increase the proportion of mothers who exclusively breastfeed their infants through age 3 months to 60% and through age 6 months to 25%. Exclusive breastfeeding is defined as an infant receiving only breast milk and no other liquids or solids except for drops or syrups consisting of vitamins, minerals or medicines (WHO, 1991). Clearly, the target for partial breastfeeding may be more ambitious, so that the target may not be so very far from the theoretical optimum, advocated by WHO. See acknowledgements on page Si.
  14 in total

1.  Infertility, fertility drugs, and ovarian cancer: a pooled analysis of case-control studies.

Authors:  Roberta B Ness; Daniel W Cramer; Marc T Goodman; Susanne Krûger Kjaer; Kathy Mallin; Berit Jul Mosgaard; David M Purdie; Harvey A Risch; Ronald Vergona; Anna H Wu
Journal:  Am J Epidemiol       Date:  2002-02-01       Impact factor: 4.897

Review 2.  Reproductive factors and breast cancer.

Authors:  J L Kelsey; M D Gammon; E M John
Journal:  Epidemiol Rev       Date:  1993       Impact factor: 6.222

3.  Role of parity and human papillomavirus in cervical cancer: the IARC multicentric case-control study.

Authors:  Nubia Muñoz; Silvia Franceschi; Cristina Bosetti; Victor Moreno; Rolando Herrero; Jennifer S Smith; Keerti V Shah; Chris J L M Meijer; F Xavier Bosch
Journal:  Lancet       Date:  2002-03-30       Impact factor: 79.321

4.  Age at first birth, parity and risk of breast cancer: a meta-analysis of 8 studies from the Nordic countries.

Authors:  M Ewertz; S W Duffy; H O Adami; G Kvåle; E Lund; O Meirik; A Mellemgaard; I Soini; H Tulinius
Journal:  Int J Cancer       Date:  1990-10-15       Impact factor: 7.396

Review 5.  Prevention of cancers of the breast, endometrium and ovary.

Authors:  Malcolm C Pike; Celeste Leigh Pearce; Anna H Wu
Journal:  Oncogene       Date:  2004-08-23       Impact factor: 9.867

6.  Characteristics relating to ovarian cancer risk: collaborative analysis of 12 US case-control studies. II. Invasive epithelial ovarian cancers in white women. Collaborative Ovarian Cancer Group.

Authors:  A S Whittemore; R Harris; J Itnyre
Journal:  Am J Epidemiol       Date:  1992-11-15       Impact factor: 4.897

Review 7.  The causes of cancer: quantitative estimates of avoidable risks of cancer in the United States today.

Authors:  R Doll; R Peto
Journal:  J Natl Cancer Inst       Date:  1981-06       Impact factor: 13.506

8.  Serous ovarian, fallopian tube and primary peritoneal cancers: a comparative epidemiological analysis.

Authors:  Susan J Jordan; Adèle C Green; David C Whiteman; Suzanne P Moore; Christopher J Bain; Dorota M Gertig; Penelope M Webb
Journal:  Int J Cancer       Date:  2008-04-01       Impact factor: 7.396

9.  Differential effects of reproductive factors on the risk of pre- and postmenopausal breast cancer. Results from a large cohort of French women.

Authors:  F Clavel-Chapelon
Journal:  Br J Cancer       Date:  2002-03-04       Impact factor: 7.640

10.  Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease.

Authors: 
Journal:  Lancet       Date:  2002-07-20       Impact factor: 79.321

View more
  11 in total

1.  Variations in reproductive events across life: a pooled analysis of data from 505 147 women across 10 countries.

Authors: 
Journal:  Hum Reprod       Date:  2019-05-01       Impact factor: 6.918

2.  A methodologic framework to evaluate the number of cancers attributable to lifestyle and environment in Alberta.

Authors:  Anne Grundy; Christine M Friedenreich; Abbey E Poirier; Farah Khandwala; Darren R Brenner
Journal:  CMAJ Open       Date:  2016-09-15

3.  Polymorphisms of the XRCC1 gene and breast cancer risk in the Mexican population.

Authors:  Nelly M Macías-Gómez; Valeria Peralta-Leal; Juan Pablo Meza-Espinoza; Melva Gutiérrez-Angulo; Jorge Durán-González; Juan Manuel Ramírez-González; Alejandra Gaspar-Del Toro; Adolfo Norberto-Rodríguez; Evelia Leal-Ugarte
Journal:  Fam Cancer       Date:  2015-09       Impact factor: 2.375

4.  Cancer incidence attributable to lifestyle and environmental factors in Alberta in 2012: summary of results.

Authors:  Anne Grundy; Abbey E Poirier; Farah Khandwala; Xin Grevers; Christine M Friedenreich; Darren R Brenner
Journal:  CMAJ Open       Date:  2017-07-07

5.  Breast cancer incidence in a cohort of U.S. flight attendants.

Authors:  Mary K Schubauer-Berigan; Jeri L Anderson; Misty J Hein; Mark P Little; Alice J Sigurdson; Lynne E Pinkerton
Journal:  Am J Ind Med       Date:  2015-03       Impact factor: 2.214

6.  The Relationship Between Breast Cancer and Risk Factors: A Single-Center Study.

Authors:  Arzu Ozsoy; Nurdan Barca; Betul Akdal Dolek; Hafize Aktaş; Eda Elverici; Levent Araz; Ozlen Ozkaraoğlu
Journal:  Eur J Breast Health       Date:  2017-04-04

7.  Birth weight and prepubertal body size predict menarcheal age in India, Peru, and Vietnam.

Authors:  Elisabetta Aurino; Whitney Schott; Mary E Penny; Jere R Behrman
Journal:  Ann N Y Acad Sci       Date:  2017-09-28       Impact factor: 5.691

8.  Cancers in Australia in 2010 attributable to total breastfeeding durations of 12 months or less by parous women.

Authors:  Susan J Jordan; Louise F Wilson; Christina M Nagle; Adele C Green; Catherine M Olsen; Christopher J Bain; Nirmala Pandeya; David C Whiteman; Penelope M Webb
Journal:  Aust N Z J Public Health       Date:  2015-10       Impact factor: 2.939

Review 9.  Life-course origins of the ages at menarche and menopause.

Authors:  Michele R Forman; Lauren D Mangini; Rosenie Thelus-Jean; Mark D Hayward
Journal:  Adolesc Health Med Ther       Date:  2013-01-18

10.  The association between the 844ins68 polymorphism in the CBS gene and breast cancer.

Authors:  Martha Patricia Gallegos-Arreola; Luis Eduardo Figuera-Villanueva; Adriana Ramos-Silva; Efraín Salas-González; Ana María Puebla-Pérez; Valeria Peralta-Leal; José Elías García-Ortiz; Ingrid Patricia Dávalos-Rodríguez; Guillermo Moisés Zúñiga-González
Journal:  Arch Med Sci       Date:  2014-12-22       Impact factor: 3.318

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.