Intrauterine environments and breast cancer risk: meta-analysis and systematic review

bcr1850 BCJ Research article Intrauterine environments and breast cancer risk: meta-analysis and systematic review Park Kyung Sue suepark@snu.ac.kr Kang Daehee dhkang@snu.ac.kr McGlynn A Katherine mcglynnk@mail.nih.gov Garcia-Closas Montserrat garciacm@exchange.nih.gov Kim Yeonju kyju@snu.ac.kr Yoo Young Keun kyyoo@plaza.snu.ac.kr Brinton A Louise brintonl@exchange.nih.gov

Department of Preventive Medicine, Seoul National University College of Medicine, Yeongeon-dong, Jongro-gu, Seoul 110-799, Seoul, Republic of Korea

Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Executive Blvd, Rockville, Maryland 20892-7234, USA

Cancer Research Institute, Seoul National University, Yeongeon-dong, Jongro-gu, Seoul 110-799, Seoul, Republic of Korea

National Cancer Center, Madu1-Dong, Ilsandong-Gu, Goyang-Si, Gyeonggi-Do 410-769, Republic of Korea

Breast Cancer Research 1465-5411 2008 10 1 R8 http://breast-cancer-research.com/content/10/1/R8 18205956 10.1186/bcr1850 20 7 2007 23 8 2007 30 9 2007 21 1 2008 21 01 2008 2008 Park et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Introduction

Various perinatal factors, including birth weight, birth order, maternal age, gestational age, twin status, and parental smoking, have been postulated to affect breast cancer risk in daughters by altering the hormonal environment of the developing fetal mammary glands. Despite ample biologic plausibility, epidemiologic studies to date have yielded conflicting results. We investigated the associations between perinatal factors and subsequent breast cancer risk through meta-analyses.

Methods

We reviewed breast cancer studies published from January 1966 to February 2007 that included data on birth weight, birth order, maternal age, gestational age, twin status, and maternal or paternal smoking. Meta-analyses using random effect models were employed to summarize the results.

Results

We found that heavier birth weights were associated with increased breast cancer risk, with studies involving five categories of birth weight identifying odds ratios (ORs) of 1.24 (95% confidence interval [CI] 1.04 to 1.48) for 4,000 g or more and 1.15 (95% CI 1.04 to 1.26) for 3,500 g to 3,999 g, relative to a birth weight of 2,500 to 2,599 g. These studies provided no support for a J-shaped relationship of birthweight to risk. Support for an association with birthweight was also derived from studies based on three birth weight categories (OR 1.15 [95% CI 1.01 to 1.31] for ≥4,000 g relative to <3,000 g) and two birth weight categories (OR 1.09 [95% CI 1.02 to 1.18] for ≥3,000 g relative to <3,000 g). Women born to older mothers and twins were also at some increased risk, but the results were heterogeneous across studies and publication years. Birth order, prematurity, and maternal smoking were unrelated to breast cancer risk.

Conclusion

Our findings provide some support for the hypothesis that in utero exposures reflective of higher endogenous hormone levels could affect risk for development of breast cancer in adulthood.

Introduction

Intrauterine environmental exposures to endogenous or exogenous hormones, notably estrogens, may influence the subsequent development of breast cancer in offspring 1. During pregnancy, levels of circulating estrogens and other hormones with growth-enhancing properties are at least 10 times higher than those in nonpregnant women, with increases seen with advancing gestational age 234. The hypothesis that breast cancer in daughters may be influenced by the intrauterine environment is receiving increased attention 5. Perinatal factors, including birth weight, birth order, maternal age, gestational age, twin status, and parental smoking, have been postulated as risk factors for breast cancer through altered hormonal influences on the developing fetal mammary glands 1. Despite ample biologic plausibility, this hypothesis is difficult to evaluate directly 5, and previous epidemiologic studies have reported conflicting results 67.

Here we review the epidemiologic studies that have assessed the association between perinatal factors and breast cancer risk in daughters. A meta-analytical approach was applied in order to clarify further the possible role played by the intrauterine environment in the etiology of breast cancer.

Materials and methods

Identification of studies

The data retrieved for the systematic review were based on searches of all published papers, letters, abstracts, and review articles on birth weight, birth order, maternal age, gestational age, twin status, and maternal or paternal smoking and breast cancer using the MEDLINE database from January 1966 through February 2007. We used keywords combining text words, with terms for six perinatal factors combined with terms for breast cancer (Table 1). We also manually searched the reference lists of all studies that fulfilled the inclusion criteria for further relevant publications. Articles were included in our systematic review if they fulfilled the following three criteria: the exposure status of at least one of six perinatal risk factors of interest was compared with nonexposure status; the outcome focused on the daughter's breast cancer morbidity or mortality using an epidemiologic study design (case-control design, data linkage study, or cohort study design); and the article was written in English language. We excluded animal studies, investigations focusing on male breast cancer, reviews, and studies that did not provide separate relative risks for breast cancer. We also excluded studies if odds ratios (ORs) or relative risks (RRs) were not specifically provided, raw data were not available for calculation of risks, or the emphasis of analyses was on hazard ratios or standardized incidence ratios.

Table 1

Search terms used in systematic review

Subject

Search term

Breast neoplasm

Breast neoplasms, subsequent breast neoplasm, breast neoplasm and daughter

Birth weight

Cirth weight, birthweight, birth size

Birth order

Birth order, birth rank

Maternal age

Maternal age, mother's age, parental age

Gestational age

Gestational age, preterm, prematurity, abruption placenta, pre-eclampsia, eclampsia

Twinship

Twin, twining, multiple births, multiple pregnancy, monozygote twin, dizygote twin,

Parental smoking

Maternal smoking, mother's smoking, paternal smoking, father's smoking, parental smoking

Others

Prenatal factors, perinatal factors, intrauterine environment, intrauterine factor, In-utero exposure

Statistical analyses

For the purposes of meta-analysis, birth weight was classified in three different ways: five categories (<2,500 g, 2,500 to 2,999 g [referent], 3,000 to 3,499 g, 3,500 to 3,999 g, and ≥4,000 g); three categories (<3,000 g [referent], 3,001 to 3,999 g, and ≥4,000 g); and two categories (<3,000 g [or ≤3,000 g; referent] and ≥3,000 g [or >3,000 g]). Birth order was examined using two different categorical schemes: 1 (referent) versus ≥2; and 1 (referent), 2 to 4, and ≥5. Maternal age was classified into three categories: <25 years old (referent), 25 to 29 years old, and ≥30 years old. Gestational age was also analyzed in two ways: ≤36 weeks versus ≥37 weeks (referent); and ≤32 weeks versus ≥33 weeks (referent). To examine twin status, three classification schemes were employed: twin versus singleton (referent); monozygotic twin (or sister twins if zygosity was not reported) versus singleton (referent); and dizygotic twin (or sister-brother twins if zygosity was not reported) versus singleton (referent). Maternal or paternal smoking was considered as follows: no smoking during pregnancy (referent) versus smoking during pregnancy. If the criteria utilized in an article were slightly different from our criteria, then we included the data and described the difference in a footnote.

ORs and 95% confidence intervals (CIs) were recalculated from published frequency tables of individual studies using the Mantel-Haenszel common OR estimate. However, the reported OR (95% CI) was used when the published studies did not provide further details as to the frequencies of the exposure variables. If the manuscript reported the results after performing a stratified analysis, then we re-calculated the crude OR by combining across strata. A random-effects model was used to obtain summary ORs and 95% CIs.

Heterogeneity was assessed by heterogeneity test using Cochran Q statistics 8. Publication bias was assessed according to the Egger regression asymmetry test, and the Begg and Mazumdar adjusted rank correlation tests 910. The Egger test is a simple linear regression of the natural log of ORs or RRs against its precision (the inverse of its standard error) 10. The Begg and Mazumdar rank correlation test reports the rank correlation (Kendall's tau) between the standardized effect size and the standard errors of these effects. If asymmetry is caused by publication bias, then we would expect that high standard errors (small studies) would be associated with larger effect sizes (ORs or RRs) or low standard errors (large studies) would be associated with smaller effect sizes 9. The Begg and Mazumdar test makes fewer assumptions than does the Egger test, but it is insensitive to many types of bias (lower power) that the Egger test is sensitive to 11.

When significant heterogeneity or publication bias was found, we performed subgroup analyses by study design (case-control study versus cohort study), and the source of information (data linkage versus self-report) to assess the impact on between-study variations (heterogeneity). Many of the large-scale studies, especially cohort studies, were published after 2000; thus, we classified publication years into before 2000 versus 2000 or later in order to assess publication biases associated with small study sizes. Few studies focused on either Asians or African-Americans, and so it was not possible to examine ethnicity effects. All statistical analyses were conducted using STATA (Version 8.2 [special edition]; Stata Corp., College Station, TX, USA).

Results

We identified 34 studies that assessed the association between birth weight and breast cancer risk (Table 2): 19 case-control studies (eight population based, three nested, six record linkage based, and two twin-based) and 15 cohort studies (seven population based and eight record linkage based). Many studies showed positive association between heavier birth weight and breast cancer risk 1213141516171819202122232425262728293031, and some of the studies observed stronger effects among younger (<45 years) or premenopausal women 14222930. In contrast, studies observing no association 32333435363738394041 or a negative one 42434445 also have been reported. Additionally, some authors reported a J-shaped relationship between birth weight and breast cancer risk 121415182533353745, particularly for early-onset cancers 18.

Table 2

Studies assessing the association of birth weight and the risk for breast cancer

Type of study

Ref.

Year

Design

Cases

Controls (or cohort)

Country/place of study

Birthweight (g)

OR (95% CI)

Comments

Case-control studies

[42]

1988

PCC

153

461

USA

1,162–2,948

Referent

Matched analysis; P for trend = 0.41

2,949–3,340

0.65 (0.33–1.26)

3,341–4,451

0.76 (0.41–1.43)

[12]^a

1992

LCC

458

1,197

Sweden

<2,500

1.18 (0.60–2.33)

Adjusted for age and birth date

2,500–2,999

Referent

3,000–3,499

1.29 (0.90–1.91)

3,500–3,999

1.47 (1.00–2.18)

≥ 4,000

1.23 (0.80–2.00)

[13]

1996

NCC

550

1,478

USA

<2,500

0.56 (0.34–0.93)

Adjusted for age

2,500–2,999

0.68 (0.47–0.99)

3,000–3,499

0.71 (0.50–0.99)

3,500–3,999

0.85 (0.59–1.22)

≥ 4,000

Referent

[14]

1996

PCC

922

1,194

USA

Age 21–45 years:

Adjusted for age, menopausal status, and maternal smoking; P for trend = 0.06 among both groups. The OR (95% CI) for birth weight ≥ 4,000 g among patients with early-onset breast cancer (≤ 30 years old) was 3.3 (1.0–11.0)

<2,500

1.3 (0.9–2.0)

2,500–2,999

Referent

3,000–3,499

1.3 (1.0–1.7)

3,500–3,999

1.2 (0.8–1.6)

≥ 4,000

1.7 (1.1–2.5)

Age 50–64 years:

<2,500

0.9 (0.5–1.7)

2,500–2,999

Referent

3,000–3,499

1.1 (0.7–1.7)

3,500–3,999

0.8 (0.4–1.3)

≥ 4,000

0.6 (0.3–1.1)

[32]

1997

NCC

1068

2,027

Sweden

<2,500

0.80 (0.50–1.26)

Adjusted for maternal age, socioeconomic status, parity, and pre-eclampsia or eclampsia, neonatal jaundice, severe prematurity, and twinship

2,500–2,999

Referent

3,000–3,499

1.00 (0.79–1.28)

3,500–3,999

0.99 (0.77–1.26)

≥ 4,000

1.04 (0.77–1.41)

[33]

1998

PCC

510

436

USA

<2,500

1.2 (0.7–2.1)

Crude ORs

2,500–2,999

Referent

3,000–3,499

1.0 (0.7–1.5)

3,500–3,999

1.0 (0.7–1.5)

≥ 4,000

1.3 (0.7–2.3)

[15]

2000

LCC

484

2,870

USA

<1,500

1.59 (0.61–4.11)

Crude ORs

1,500–2,499

1.33 (0.94–1.90)

2,500–3,499

Referent

3,500–4,499

1.08 (0.87–1.34)

≥ 4,500

3.29 (1.37–7.92)

[34]

2001

LTCC

Sweden

<1,999

Referent

Matched analysis by conditional logistic regression

2,000–2,499

1.6 (0.6–4.0)

2,599–2,999

2.4 (0.9–6.2)

≥ 3,000

1.6 (0.4–5.6)

(P trend = 0.05)

[43]

2001

LCC

319

768

USA

<2,500

1.4 (0.55–3.4)

Crude ORs. Higher birth weight (≥ 3,500 g) carried a marginal significantly higher risk for breast cancer (OR 1.76 [95% CI 0.90–3.35]) relative to lower birth weight (<3,500 g)

2,500–3,750

Referent

≥ 3,750

0.9 (0.50–1.6)

[16]

2001

LTCC

Sweden

≤ 2,000

Referent

Crude ORs. Study subjects were women with opposite-sexed pair twins

2,001–2,500

3.2 (0.8–12.6)

2,501–3,000

3.5 (1–13)

3,001–3,500

5.8 (1.3–25.7)

≥ 3,501

12.1 (1.1–138.8)

[35]

2002

PCC

2,088

2,187

USA

<2,500

1.10 (0.90–1.35)

Adjusted for age and residential regions (states)

2,500–2,999

0.90 (0.70–1.10)

3,000–3,499

Referent

3,500–3,999

1.07 (0.90–1.30)

4,000–4,499

0.89 (0.70–1.14)

≥ 4,500

1.18 (0.90–1.51)

[44]

2002

PCC

288

350

China

<2,500

0.9 (0.4–2.0)

Adjusted for age income, family history of breast cancer in first-degree relative, history of fibroadenoma, age at menarche, parity, and age at first live birth.

2,500–2,999

Referent

3,000–3,499

1.1 (0.8–1.6)

3,500–3,999

0.8 (0.4–1.4)

≥ 4,000

0.7 (0.4–1.4)

[17]

2002

LCC

373

1,150

USA

<3,090

Referent

Adjusted for parity and age at first birth. P for trend = 0.02

3,090–3,410

1.1 (0.8–1.5)

3,420–3,720

1.2 (0.9–1.6)

≥ 3,630

1.4 (1.1–1.9)

[18]

2003

LCC

881

3,423

Denmark

<2,500

1.66 (1.00–2.51)

Adjusted for mother's marital status, maternal age, and birth order

2,500–2,999

0.83 (0.60–1.10)

3,000–3,499

Referent

3,500–3,999

0.98 (0.80–1.17)

≥ 4,000

1.25 (1.00–1.55)

[19]

2004

NCC

238

Sweden

100 g increase

1.06 (1.00–1.12)

Adjusted for gestational age, birth year, and maternal hypertension/proteinuria

[45]

2004

LCC

2471

9801

USA

<1,500

0.64 (0.40–1.11)

Adjusted for age and maternal age at first birth

1,500–1,999

1.05 (0.70–1.68)

2,000–2,499

1.02 (0.80–1.31)

2,500–3,499

Referent

3,500–3,999

0.97 (0.90–1.08)

4,000–4,499

0.93 (0.80–1.11)

≥ 4,500

0.69 (0.40–1.09)

[36]

2004

PCC

196

167

USA

All subjects:

Adjusted for age, race and sampling fractions, body mass index, household income, and maternal age. Tertiles are race specific with cutpoints derived from controls. White women: <3,062, 3,062–3,458, >3,458 g; black women: <3,146, 3,146–3,488, >3,488 g. Restricted data using birth weight measured in pounds and ounces and participant delivered in a medical facility by a physician

Lower tertile

1.0 (0.6–1.7)

Central tertile

Referent

Upper tertile

0.7 (0.4–1.2)

White, restricted

data:

Lower tertile

1.1 (0.5–2.4)

Central tertile

Referent

Upper tertile

1.4 (0.6–2.0)

[20]

2006

PCC

2,386

2,502

Poland

<2,500

Referent

Adjusted for: age, education, age at menarche, menopausal status and age at menopause, age at first full-term pregnancy, number of full-term pregnancies, family history of breast cancer among first-degree relatives, mammography screening, and current body mass index. Lower birth weight (<2,500 g) carries greater risk than birth weight of 2,500–4,000 g among women under 45 years old

2,500–4,000

1.22 (0.92–1.62)

>4,000

1.54 (1.08–2.19)

(p-trend = 0.01)

[37]

2006

PCC

1,166

2,105

USA

<2,495

1.19 (0.85–1.66)

Adjusted for age (years), education (years), race, body mass index, history of breast benign disease, family history of breast cancer, lactation (months), age at menarche (years), age at first full-term pregnancy (years), age at menopause (years), parity

2,495–3,130

Referent

3,131–3,855

0.97 (0.75–1.25)

>3,855

1.03 (0.74–1.44)

Cohort studies

[21]

1999

LCohort

152,590

Sweden

<2,500

Referent

Standardization for sex, age, and age-specific incidence rate

2,500–3,999

1.3 (0.6–2.4)

4,000–4,499

1.2 (0.0–6.7)

≥ 4,500

1.3 (0.7–2.3)

[22]

2000

Cohort

2,221

All ages

Adjusted for age. P for trend = 0.03 among premenopausal women

<3,000

Referent

3,000–3,499

1.05 (0.41–2.71)

3,500–3,999

1.76 (0.72–4.33)

≥ 4,000

2.02 (0.59–6.90)

Premenopausal ages

<3,000

Referent

3,000–3,499

1.99 (0.40–9.86)

3,500–3,999

3.26 (0.69–15.36)

≥ 4,000

5.65 (0.95–33.84)

[38]

2001

LCohort

177

3,447

Sweden

≤ 2,000

Referent

Crude hazard ratios

2,001–2,500

1.4 (0.6–3.4)

2,501–3,000

1.9 (0.8–4.3)

3,001–3,500

1.5 (0.6–3.5)

≥ 3,501

1.9 (0.7–5.0)

[39]

2001

Cohort

1260

Sweden

≤ 3,000

Referent

Singleton only; adjusted for gestational age and cohort membership

3,010–3,349

1.16 (0.47–2.87)

3,350–3,590

1.65 (0.71–3.86)

3,600–3,960

1.58 (0.67–3.72)

≥ 4,000

1.57 (0.67–3.64)

[23]

2003

LCohort

5,352

Sweden

<3,000

Referent

Crude ORs;P for trend = 0.01

3,000–3,499

1.46 (0.60–3.43)

3,500–3,999

2.09 (0.90–4.85)

≥ 4,000

2.78 (1.10–7.15)

[24]

2003

LCohort

2,334

106,504

Denmark

1,000 g increase

9 (0.02–17)%

Adjusted for age and calendar period. Additional adjustment for parity and age at first birth did not indicate confounding

[25]

2003

LCohort

1483

Sweden

500–1,999

1.14 (0.70–1.85)

Standardized incidence ratio (expected/observed)

2,000–2,999

0.71 (0.40–1.15)

≥ 3,000

2.55 (1.03–5.25)

[26]^a

2004

LCohort

2,074

91,601

Denmark

Median of each quintile

Adjusted for age and calendar period. No change in estimates when additionally adjusted for parity and age at first birth

2.5

Referent

3.0

0.98 (0.85–1.13)

3.4

1.06 (0.93–1.20)

3.6

1.05 (0.87–1.27)

4.0

1.17 (1.02–1.33)

[27]

2004

Cohort

2,176

<3,000

Referent

Adjusted for age; P for trend = 0.03

3,000–3,499

1.37 (0.34–5.47)

3,500–3,999

2.18 (0.58–8.21)

≥ 4,000

5.03 (1.13–22.47)

[28]

2005

LCohort

311

16,011

USA

<3,040

Referent

Adjusted for year of birth

3,040–3,310

1.4 (1.0–2.1)

3,320–3,550

1.0 (0.6–1.5)

3,560–3,830

1.3 (0.9–1.9)

≥ 3,840

1.5 (1.0–2.2)

[29]^a

2005

LCohort

367

5,346

Sweden

<50 years

<3,000

Referent

3,000–3,499

1.81 (0.77–4.26)

3,500–3,999

2.66 (1.09–6.46)

≥ 4,000

4.00 (1.49–10.72)

≥ 50 years

<3,000

Referent

3,000–3,499

0.86 (0.62–1.19)

3,500–3,999

1.06 (1.20–3.34)

≥ 4,000

0.91 (0.57–1.46)

[40]

2006

Cohort

5,847

USA

<3,000

0.98 (0.61–1.60)

Adjusted for age

3,000–3,499

Referent

≥ 3,500

1.09 (0.66–1.80)

[30]

2006

Cohort

3,140

91,601

USA

Premenopause

Adjusted for age: P for trend = 0.019

<2,495

0.69 (0.50–0.94)

2,495–3,130

0.79 (0.64–0.97)

3,131–3,810

0.76 (0.63–0.93)

>3,810

Referent

Postmenopause:

Adjusted for age: P for trend = 0.99

<2,495

1.04 (0.88–1.23)

2,495–3,130

1.00 (0.87–1.14)

3,131–3,855

1.05 (0.93–1.20)

>3,855

Referent

[31]

2006

Cohort

209

1,024

USA

<2,500

0.9 (0.5–1.6)

Hazard ratio; adjusted for age at diagnosis, diagnosis year, stage at diagnosis, and birth order, with exception of birth order, which is adjusted for maternal age

2,500–3,999

Referent

≥ 4,000

1.8 (1.0–3.1)

(P trend = 0.1)

[41]

2007

Cohort

657

38,566

Sweden

<2,500

0.65 (0.43–0.99)

Adjusted for adult body mass index

2,500–3,000

1.04 (0.86–1.25)

>3,000

Referent

Cohort, cohort study; LCC, case-control study with linkage with population and cancer registry data; LCohort, cohort study with linkage with population and cancer registry data; LTCCS, twin case-control study by using linkage with birth and cancer registry data; NCC, nested case-control study in cohort; PCC, population-based case-control study. ^aThe numbers of cases and controls were not shown in the original article.

Among 34 studies of birth weight and breast cancer, we selected studies that employed the same categories of birth weight. To evaluate whether a J-shaped relationship existed, we grouped birth weight into more than three categories. The findings of meta-analysis of eight studies that utilized five categories of birth weight (<2,500, 2,500 to 2,999, 3,000 to 3,499, 3,500 to 3,999, and ≥4,000 g) and 11 studies that used three categories (<3,000, 3,000 to 3,999, and ≥4,000 g) are shown in Figures 1 and 2. To include more studies, we also categorized birthweights as <3,000 g (or ≤3,000 g) and ≥3,000 g (or >3,000 g; Figure 3). Sixteen studies among all 34 studies were included in the meta-analyses for birth weight and breast cancer: seven studies 13141832333544 were included in the all three meta-analyses; four studies 22232739 were included in the two of the three meta-analyses; and five studies were included in only one meta-analysis 1216283438. There was no significant heterogeneity across studies (P_Q test > 0.05 for all categories). In the five-category meta-analysis, ORs were 1.11 (95% CI 0.90 to 1.33) for birth weight <2,500 g, 1.11 (0.99 to 1.25) for 3,000 to 3,499 g, 1.15 (1.04 to 1.26) for 3,500 to 3,999 g, and 1.24 (1.04 to 1.48) for ≥4,000 g relative to the referent category of 2,500 to 2,999 g. In the three-category meta-analysis, ORs were 1.06 (95% CI 0.98 to 1.14) for 3,000 to 3,999 g and 1.15 (1.01 to 1.31) for ≥4,000 g relative to the referent category of <3,000 g. In the two-category meta-analysis, ORs were 1.09 (95% CI 1.02 to 1.18) for the category of >3,000 g (or ≥3,000 g) relative to the referent category of ≤3,000 g (or <3,000 g).

We identified 17 studies (15 case-control and two cohort) that assessed the association between birth order and breast cancer risk (Table 3). Eight of the studies reported an inverse relationship 1420313536424647. Some studies found significantly lower risks for second or later born children versus first-born children 3146. Some studies found significantly or marginally significantly reduced risk among women whose birth had been preceded by the birth of at least five siblings 2035. Other several studies noted an increased risk associated with higher birth order 15374849, whereas some studies failed to observe such an association 12183250. One study did not supply the estimated risk but describe the P value by the mean difference of birth order 51.

Table 3

Studies assessing the association of birth order and the risk of breast cancer

Type of study

Ref.

Year

Design

Cases

Controls (or cohort)

Country/place of study

Birth order

OR (95% CI)

Comments

Case-control studies

[51]

1967

LCC-D

229

USA

The authors measured the mean value of birth weight instead of providing ORs (95% CIs). The mean difference between cases and matched controls was not significant (P > 0.2). They provided the frequency of each case and control in the tables and we calculated crude ORs

≥ 7

[50]^a

1980

MCC

4339

12,760

USA, Japan, Slovenia, Athens, Taipei

Referent

The risks (point estimates) only by birth order were shown in the figure in the original article.

0.93

1.08

0.99

1.05

1.07

1.18

≥ 8

1.02

[42]

1988

PCC

153

461

USA

Referent

P for trend = 0.16

0.92 (0.55–1.54)

0.98 (0.58–1.72)

0.69 (0.36–1.32)

≥ 5

1.03 (0.60–1.79)

[46]

1991

MCC

927

2,616

USA/Wales/Japan

All ages

Adjusted for age, study center, parity, age at first birth, age at menarche, height, body mass index, maternal age at birth, and menopausal status

Referent

0.91 (0.73–1.02)

1.11 (0.87–1.27)

≥ 4

1.09 (0.81–1.18)

Premenopausal

Referent

≥ 2

0.76 (0.60–0.96)

[12]

1992

LCC

458

1,197

Sweden

Referent

Adjusted for age and birth date

≥ 2

1.00 (0.76–1.32)

[47]

1994

PCC

2,414

9,138

USA

Referent

Adjusted for age at first birth and number of children

0.90 (0.78–1.03)

0.98 (0.84–1.14)

0.86 (0.73–1.02)

0.93 (0.78–1.11)

1.02 (0.84–1.23)

0.91 (0.73–1.14)

≥ 8

0.88 (0.75–1.04)

[14]

1996

PCC

1,129

1,393

USA

Referent

Adjusted for age, menopausal status, and maternal smoking; P for trend = 0.06 among both groups

1.0 (0.7–1.4)

≥ 3

0.8 (0.6–1.1)

[32]

1997

NCC

1,068

2,727

Sweden

Referent

Adjusted for maternal age, socioeconomic status, parity, and preeclampsia or eclampsia, neonatal jaundice, severe prematurity, and twinship

1.01 (0.83–1.22)

≥ 3

1.01 (0.81–1.26)

[15]

2000

LCC

481

2,863

USA

1.07 (0.84–1.35)

Crude ORs

2–3

Referent

4–5

1.06 (0.81–1.38)

≥ 6

1.50 (1.06–2.13)

[35]

2002

PCC

1,555

1,539

USA

Referent

Adjusted for age and residential regions (states)

1.07 (0.88–1.30)

1.07 (0.85–1.35)

1.01 (0.77–1.31)

0.66 (0.48–0.92)

≥ 6

0.81 (0.62–1.08)

[18]

2003

LCC

881

3,423

Denmark

Referent

Adjusted for mother's marital status, maternal age, and birth order

≥ 2

1.01 (0.83–1.12)

[36]

2004

PCC

854

785

USA

All subjects

Adjusted for age, race and sampling fractions, body mass index, hosehold income, maternal age

Referent

2–4

0.9 (0.7–1.1)

≥ 5

1.0 (0.8–1.3)

Born ≥ 1948

Referent

2–4

0.9 (0.6–1.4)

≥ 5

0.6 (0.3–1.3)

[48]^a

2005

MCC

Nigeria

≤ 3

Referent

Crude ORs

≥ 4

1.50 (0.25–8.98)

[20]

2005

PCC

1642

1,713

Poland

Referent

Adjusted for age, education, age at menarche, menopausal status and age at menopause, age at first full-term pregnancy, number of full-term pregnancies, family history of breast cancer among first-degree relatives, mammography screening, and current body mass index

1.07 (0.91–1.24)

3–5

0.99 (0.85–1.15)

≥ 6

0.81 (0.61–1.06)

P for trend = 0.81

[37]

2006

PCC

1,166

2,105

USA

Referent

≥ 2

1.27 (0.88–1.85)

Cohort studies

[31]

2006

Cohort

209

1,024

USA

Referent

Hazard ratio for breast cancer mortality: adjusted for age at diagnosis, diagnosis year, stage at diagnosis, and birth order, with exception of birth order, which is adjusted for maternal age

0.2 (0.2–0.3)

≥ 3

0.2 (0.2–0.3)

P for trend < 0.01

[49]^a

2001

Cohort

Sweden

Continuous scale

1.05 (1.01–1.10)

^aWe did not include these studies in the meta-analysis because they employed different categories or a continuous scale, or they did not provide the numbers of cases and controls in the original article. Cohort, cohort study; LCC, case-control study with linkage with population and cancer registry data; LCC-D, case-control study with linkage with population and cancer death certification data; MCC, multicenter case-control study; NCC, nested case-control study in cohort; PCC, population-based case-control study.

Figure 1

Meta-analysis of the association between birth weight (five categories) and risk for breast cancer

Meta-analysis of the association between birth weight (five categories) and risk for breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows. Category I (birth weight <2,500 g) versus reference: Q = 9.66 (8 degrees of freedom), P = 0.29; Begg test, P = 0.75; Egger test, P = 0.66. Category II (2,500 to 2,999 g) is the reference. Category III (3,000 to 3,499 g) versus reference: Q = 6.53 (8 degrees of freedom), P = 0.59; Begg test, P = 0.25; Egger test, P = 0.46. Category IV (3,500 to 3,999 g) versus reference: Q = 4.17 (8 degrees of freedom), P = 0.84; Begg test, P = 0.60; Egger test, P = 0.93. Category V (≥4,000 g) versus reference: Q = 11.18 (8 degrees of freedom), P = 0.19; Begg test, P = 0.25; Egger test, P = 0.30. ¹We used adjusted odds ratios (ORs) for meta-analysis because the numbers of cases and controls were not represented in the original article. CI, confidence interval.

Figure 2

Meta-analysis of the association between birth weight (three categories) and risk for breast cancer

Meta-analysis of the association between birth weight (three categories) and risk for breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows. Category I (birth weight 3,000 to 3,999 g) versus reference (<3,000 g): Q = 4.97 (11 degrees of freedom), P = 0.93; Begg test, P = 0.54; Egger test, P = 0.27. Category II (≥4,000 g) versus reference: Q = 13.44 (11 degrees of freedom), P = 0.27; Begg test, P = 0.54; Egger test, P = 0.53. CI, confidence interval; OR, odds ratio.

Figure 3

Meta-analysis of the association between birth weight (two categories) and risk for breast cancer

Meta-analysis of the association between birth weight (two categories) and risk for breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as folows. Reference (<3,000 g [or ≤3,000 g]) versus ≥3,000 g (or >3,000 g): Q = 11.57 (15 degrees of freedom), P = 0.93; Begg test, P = 0.15; Egger test, P = 0.50. CI, confidence interval; OR, odds ratio.

For the meta-analysis, we included 14 studies (13 case-control studies and one cohort) that used two birth order categories: 1 (referent) and ≥2. There was significant heterogeneity across all studies (P_Q test < 0.01), although there was no significant heterogeneity across the case-control studies (P_Q test = 0.90). As shown in Figure 4, there was no difference in risk according to birth order across all studies (OR 0.97 [95% CI 0.91 to 1.04]) or within the case control studies (OR 0.99 [95% CI 0.94 to 1.04]). We calculated the crude odds ratio from the cohort study 31, and the result was very different from the summary OR (calculated crude OR 0.28 [95% CI 0.21 to 0.36]). The results of all case-control studies were near null, whereas the cohort study found a significant risk reduction in birth orders of 2 or greater. We also examined the seven studies that classified individuals according to three birth order levels (1 [referent], 2 to 4, ≥5; Figure. 4). There was significant heterogeneity across studies (all of which were case-control studies) for the highest birth order category (P_Q test = 0.03) Women with a birth order of ≥5 were at nonsignificantly reduced risk compared with first-born women (OR 0.88 [95% CI 0.75–1.01]). There was no difference in risk for women of birth orders 2 to 4 (OR 0.97 [95% CI 0.91–1.03]).

Figure 4

Meta-analysis of the association between birth order and risk for breast cancer

Meta-analysis of the association between birth order and risk for breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows. Category I (birth order 2+) versus reference (birth order 1): Q = 87.79 (13 degrees of freedom), P < 0.01; Begg test, P = 0.44; Egger test, P = 0.46. Category II (birth order 5+ and 2 to 4) versus reference: Q = 4.56 (6 degrees of freedom), P = 0.60; Begg test, P = 0.37; Egger test, P = 0.44. Category II (birth order ≥6, 2 to 5) versus reference: Q = 14.42 (6 degrees of freedom), P = 0.60; Begg test, P = 0.37; Egger test, P = 0.44. ¹Category I of birth order was 2+ vs 1. ²Category II of birth order was composed of two conditions: 5+ and 2 to 4; and ≥6 and 2 to 5 vs 1. ³We used adjusted odds ratios (ORs) for meta-analysis because the numbers of cases and controls were not represented in the original article. CI, confidence interval.

We identified 28 studies (22 case-control and six cohort) that assessed the association between maternal age and breast cancer risk (Table 4). Seven studies observed modestly increased risks for daughters born to older mothers 15313236424652. A pattern of slight decrease after modest increase in risk was found in five other studies 5053545556. Fourteen studies, however, no association was observed 12141820353738474957585960. Two studies did not estimate the risks 5161.

Table 4

Studies assessing the association of maternal age with risk for breast cancer

Ref.

Year

Design

Cases

Controls (or cohort)

Country/place of study

Maternal age (years)

OR (95% CI)

Comments

Case-control studies

[51]

1967

LCC-D

229

USA

≤ 19

Mean maternal age among cases was higher than that among controls (P < 0.005). The frequency of each case and control were shown in the tables provided and we calculated crude ORs

20–24

25–29

30–34

35–39

≥ 40

[61]^a

1974

PCC

308

USA

Matched analysis; the mean maternal age was 27.3 years among cases and 26.3 years among controls (P < 0.01)

[50]^b

1980

MCC

4339

12760

USA, Japan, Slovenia, Athens, Taipei

≤ 19

Referent

Authors showed point estimates of ORs without 95% CIs. The frequencies for each case and control were given in the tables provided and we calculated crude ORs

20–24

1.05

25–29

1.22

30–34

1.19

35–39

1.31

≥ 40

1.18

[53]^a

1984

MCC

1,176

England

≤ 20

Referent

Adjusted for age, social class, family history of breast cancer, age at first-term birth, past history of benign breast disease, age at menarche, menopausal status, cigarette smoking, and oral contraceptive use

21–25

1.41 (0.92–2.18)

26–30

1.19 (0.78–1.81)

31–35

1.29 (0.83–1.98)

≥ 36

1.19 (0.68–1.67)

[42]^a

1988

PCC

153

461

USA

All women

Matched analysis

15–22

1.18 (0.71–1.97)

23–26

Referent

27–30

1.22 (0.71–2.10)

31–46

1.66 (0.99–2.78)

P for trend = 0.67

Younger women

15–23

1.39 (0.65–2.95)

24–28

Referent

29–46

2.21 (1.02–4.80)

P for trend = 0.08

[52]^a

1989

PCC

801

1,573

USA

Continuous

1.24 (1.09–1.41)

Crude OR

[54]

1990

PCC

2,291

3,144

USA

≤ 19

Referent

Adjusted for age and parity, age at first pregnancy, total duration of breast feeding, race, age at menarche, menopausal status, body mass index, family history of breast cancer, and breast biopsy

20–24

0.95 (0.77–1.16)

25–29

1.13 (0.92–1.38)

30–34

1.16 (0.93–1.45)

35–39

1.46 (1.10–1.93)

≥ 40

1.20 (0.79–1.83)

[55]

1991

PCC

1761

1,116,553 person-years

USA

≤ 19

Referent

Crude ORs

20–24

1.02 (0.82–1.46)

25–29

1.12 (1.04–1.38)

30–34

1.16 (0.93–1.44)

35–39

1.17 (0.92–1.48)

≥ 40

1.08 (0.80–1.46)

[46]^a

1991

MCC

927

2616

USA, Wales, Japan

Each 5-yrs

1.06 (1.01–1.10)

Adjusted for age, study center, parity, age at first birth, age at menarche, height, BMI, maternal age at birth, and menopausal status

[12]^b

1992

LCC

458

1,197

Sweden

Each 5-year band

1.01 (0.92–1.12)

Adjusted for age and birth date. The authors estimated breast cancer risk according to each 5-year band of maternal age. The frequency of each case and control were given in the tables provided and we calculated crude ORs

[47]

1994

PCC

2,412

9,138

USA

≤ 19

Referent

Adjusted for age at first birth and number of children

20–24

1.05 (0.85–1.30)

25–29

1.10 (0.89–1.37)

30–34

1.10 (0.88–1.37)

35–39

1.09 (0.87–1.37)

≥ 40

0.99 (0.76–1.28)

[14]

1996

PCC

1,934

2,161

USA

≤ 24

Referent

Adjusted for age, menopausal status, and maternal smoking

25–29

1.0 (0.8–1.2)

30–34

0.9 (0.6–1.1)

≥ 35

1.0 (0.7–1.5)

[57]

1997

PCC

1,253

1,121

USA

≤ 19

Referent

Adjusted for age, menopausal status, age at menarche, parity, age at first birth, body mass index, past history of benign breast disease, and recent alcohol intake

20–24

0.84 (0.62–1.14)

25–29

1.02 (0.76–1.37)

30–34

0.93 (0.68–1.28)

35–39

1.16 (0.82–1.65)

≥ 40

0.92 (0.62–1.37)

[58]

1997

PCC

2,106

1,926

USA

≤ 19

Referent

Adjusted for age, study site, family history of breast cancer, breast biopsy, a combination variable including number of full-term births and age at first full-term pregnancy, age at menarche, menopausal status, body mass index, average lifetime alcohol consumption, and the number of mammograms

20–24

0.96 (0.7–1.2)

25–29

0.96 (0.7–1.2)

30–34

0.91 (0.7–1.2)

≥ 35

0.93 (0.7–1.3)

[32]^a

1997

NCC

1,067

2,725

Sweden

Each 5-year band

1.06 (0.99–1.14)

Adjusted for maternal age, socioeconomic status, parity, and pre-eclampsia or eclampsia, neonatal jaundice, severe prematurity, and twinship

[15]

2000

LCC

481

2863

USA

≤ 19

1.19 (0.83–1.72)

Crude ORs

20–24

Referent

25–29

1.26 (0.97–1.64)

30–34

1.38 (1.04–1.84)

≥ 35

1.70 (1.23–2.35)

[35]

2002

PCC

1,555

1,539

USA

≤ 19

1.02 (0.75–1.39)

Adjusted for age and state

20–24

0.98 (0.81–1.18)

25–29

Referent

30–34

1.15 (0.93–1.42)

35–39

1.22 (0.94–1.58)

≥ 40

1.27 (0.90–1.69)

[18]

2003

LCC

881

3,423

Denmark

≤ 24

Referent

Adjusted for mother's marital status, maternal age, and birth order

25–29

1.08 (0.88–1.32)

≥ 30

1.11 (0.90–1.36)

[36]^a

2004

PCC

854

785

USA

≤ 18

1.8 (0.9–3.4)

19–22

Referent

Adjusted for age, race and sampling fractions; tertiles are race specific with cutpoints derived from controls

23–27

3.0 (1.8–5.0)

≥ 28

2.5 (1.6–4.0)

[56]

2005

MCC

1,060

Korea

≤ 24

Referent

Adjusted for age, family history of breast cancer in first-or second-degree relatives, menopausal status, and lifetime estrogen exposure duration

25–29

1.2 (0.93–1.47)

30–34

1.4 (1.12–1.83)

≥ 35

1.1 (0.83–1.37)

[20]

2006

PCC

1,642

1,713

Poland

≤ 19

Referent

20–24

1.02 (0.75–1.39)

25–29

1.07 (0.79–1.46)

35–39

1.16 (0.84–1.60)

≥ 35

0.91 (0.66–1.27)

P for trend = 0.76

[37]^a

2006

PCC

1,166

2,105

USA

≤ 24

Referent

Adjusted for: age, education, race, body mass index, history of breast benign disease, family history of breast cancer, lactation, age at menarche, age at first full-term pregnancy, age at menopause, and parity

25–35

0.87 (0.67–1.13)

>35

0.87 (0.59–1.27)

Cohort studies

[59]

1995

Cohort

149

75,237

USA

≤ 24

Referent

Adjusted for age, education, menopausal status, parity, body mass index, height, smoking, and alcohol drinking

25–29

1.3 (0.8–2.0)

30–34

1.4 (0.9–2.1)

≥ 35

1.2 (0.7–2.0)

[60]

1995

Cohort

1,967

384,769

Sweden

≤ 19

Referent

Breast cancer mortality; adjusted for age

20–24

0.99 (0.82–1.21)

25–29

1.00 (0.82–1.22)

30–34

0.97 (0.79–1.18)

35–39

1.04 (0.84–1.29)

40–44

0.93 (0.71–1.21)

≥ 45

1.39 (0.91–2.13)

[49]^a

2001

Cohort

Sweden

Continuous scale

1.07 (0.91–1.27)

Adjusted for spouse age, year of diagnosis, and birth order

[38]^a

2001

Cohort

177

3,447

Filand

Continuous scale

No association

[31]

2006

Cohort

249

1,024

USA

≤ 24

Referent

Hazard ratio; adjusted for age at diagnosis, diagnosis year, stage at diagnosis, and birth order, with exception of birth order, which is adjusted for maternal age

25–29

1.2 (0.9–1.7)

30–34

1.4 (0.9–1.9)

≥ 35

1.7 (1.1–2.8)

P for trend = 0.03

^aWe did not include these studies in the meta-analysis because they employed different categories or a continuous scale, or they did not provide the numbers of cases and controls in the original article^bWe included this study in the meta-analysis because we calculated the crude OR using the number of subjects represented the original article. Cohort, cohort study; LCC, case-control study with linkage with population and cancer registry data; LCC-D, case-control study with linkage with population and cancer death certification data; MCC, multicenter case-control study; NCC, nested case-control study in cohort; PCC, population-based case-control study.

In our meta-analyses, we included the 18 studies that reported categorical data and examined three age categories (≤24 [referent], 25 to 29, and ≥30 years; Figure 5). There was, however, significant study heterogeneity (P_Q test < 0.01 for 25 to 29 years and for ≥30 years). Heterogeneity was also present across case-control studies and studies published after 2000 (P_Q test < 0.01). The ORs (95% CI) were 1.18 (1.05 to 1.11) for 25 to 29 years and 1.23 (1.07 to 1.15) for ≥30 years across all studies.

Figure 5

Meta-analysis for the association between maternal age and the risk of breast cancer

Meta-analysis for the association between maternal age and the risk of breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows. Maternal age 25 to 29 years: Q = 39.40 (17 degrees of freedom), P < 0.01; Begg test, P = 0.85; Egger test, P = 0.38, Maternal age 30+ years: Q = 67.34 (17 degrees of freedom), P < 0.01; Begg test, P = 0.88; Egger test, P = 0.07. ¹The reference for maternal age is ≤24 years old. CI, confidence interval; OR, odds ratio.

We identified 15 studies (10 case-control and five cohort) that assessed the association between prematurity and breast cancer risk (Table 5). Most studies did not observe a significant relationship 131415162025293133404245. Two studies found that extreme prematurity was associated with an increased risk (OR 3.96 [95% CI 1.46 to 10.81] for ≤32 weeks relative to ≥33 weeks 32, and SIR (standardized incidence ratio) 6.7 [95% CI 1.4 to 19.5] for <31 weeks 62). In contrast, another study 34 found that longer gestation was associated with a significantly increased risk (OR 8.4 [95% CI 1.3 to 54.4] for ≥40 weeks relative to ≤32 weeks).

Table 5

Table 5 Studies assessing the association of premature birth and the risk of breast cancer

Type of study

Author

Year

Design

Cases

Controls (or cohort)

Country/place of study

Gestational age (weeks)

OR (95% CI)

Comments

Case-control studies

[42]^a

1988

PCC

153

461

USA

25–32

1.16 (0.50–1.54)

Matched analysis

33–40

Referent

[13]^b

1996

NCC

571

1,525

USA

Categorical

Adjusted for age

Referent

38–39

0.76 (0.44–1.32)

36–37

0.96 (0.59–1.56)

Binomial

≥ 37

Referent

≤ 36

0.82 (0.37–1.82)

[14]

1996

PCC

1123

1371

USA

Nonpreterm

Referent

Adjusted for age, menopausal status, and maternal smoking

Preterm

1.1 (0.5–2.1)

[32]^a

1997

NCC

1,010

2,625

Sweden

≥ 33

Referent

Adjusted for maternal age, matermal socioeconomic status, maternal parity, maternal pre-eclampsia or eclampsia, neonatal jaundice, severe prematurity, twin, and birth weight

≤ 32

3.96 (1.46–10.81)

[33]^b

1998

PCC

502

433

USA

≥ 43

1.5 (0.8–2.6)

Crude ORs

37–42

Referent

≤ 36

0.9 (0.5–1.8)

[15]^a,b

2000

LCC

480

2,854

USA

≥ 37

Referent

Crude ORs

33–36

1.34 (0.85–2.13)

≤ 32

0.55 (0.19–1.57)

[34]^a,b

2001

LCC

Sweden

≥ 40

8.4 (1.3–54.4)

Matched analysis by conditional logistic regression

37–40

3.4 (0.7–17.0)

33–36

3.5 (0.7–17.5)

≤ 32

Referent

[25]^a

2003

LCohort

127

(1,483)

Sweden

≥ 33

1.08 (0.64–1.70)

Standardized incidence ratio (expected/observed)

≤ 32

0.92 (0.57–1.41)

[45]^a,b

2004

LCC

2,471

9,801

USA

≥ 37

Referent

Adjusted for age and maternal age at first birth

32–36

0.91 (0.72–1.13)

≤ 31

1.43 (0.90–2.28)

[20]^b

2005

PCC

1,424

1,457

Poland

≥ 37

Referent

≤ 36

1.01 (0.75–1.32)

Cohort studies

[62]^c

2000

LCohort

273

Sweden

0.2 (0.01–1.3)

Standardized incidence ratio

33–34

0.7 (0.1–2.0)

31–32

2.3 (0.7–5.3)

<31

6.7 (1.4–19.5)

[16]^c

2001

LTCCS

2,265

9,060

Sweden

33–36

Referent

Crude ORs

37–38

1.8 (0.83–4.0)

40–44

2.0 (0.88–4.6)

[29]^c

2005

LCohort

367

5,346

Sweden

1 week increase

<50 years

0.94 (0.83–1.07)

[40]^c

2006

Cohort

5,847

USA

<39

0.77 (0.42–1.4)

Adjusted for age

1.38 (0.78–2.4)

Referent

41+

1.33 (0.67–2.6)

[31]^b

2006

Cohort

249

1024

USA

≥ 43

0.7 (0.2–2.7)

Adjusted for: age at diagnosis, diagnosis year, stage at diagnosis, and birth order, with exception of birth order, which is adjusted for maternal age

37–42

Referent

<37

1.4 (0.7–2.9)

P for trend = 0.3

Cohort, cohort study; LCC, case-control study with linkage with population and cancer registry data; LTCCS, twin case-control study by using linkage with birth and cancer registry data; NCC, nested case-control study in cohort; PCC, population-based case-control study. ^aWe included this study in the meta-analysis with categories of ≥33 versus ≤32 months (reference). ^bWe included this study in the meta-analysis with categories of ≥37 versus ≤36 months (reference). ^cWe did not include these studies in the meta-analysis because they employed different categories or a continuous scale, or they did not provide the numbers of cases and controls in the report.

There was no significant heterogeneity across studies (P-Q test = 0.55), whereas we found no association between prematurity (≤36 weeks) and risk (OR 1.04 [95% CI 0.92 to 1.18]; Figure 6). However, a strong publication bias was observed (P-Egger test = 0.03 and P-Begg test = 0.11; Figure 7). A significant publication bias occurred because three studies with smaller standard errors of log RR 151634 reported RRs near 1.0, whereas five studies with larger standard errors 1320313345 reported substantially reduced RRs. When the analysis was performed for extreme prematurity (≤32 weeks), heterogeneity was also evident across the studies (P-Q test = 0.04), and the association was not significant (OR 1.20 [95% CI 0.74 to 1.95]).

Figure 6

Meta-analysis of studies assessing the association of prematurity and risk for breast cancer

Meta-analysis of studies assessing the association of prematurity and risk for breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows. Category 36+: Q = 5.91 (7 degrees of freedom), P = 0.55; Begg test, P = 0.11; Egger test, P = 0.03. Category 32+: Q = 10.10 (4 degrees of freedom), P = 0.04; Begg test, P = 0.09; Egger test, P = 0.40. ¹Category of prematurity (week): ≤36 versus ≥37 (reference). ²Category of prematurity (week): ≤32 versus ≥33 (reference). CI, confidence interval; OR, odds ratio.

Figure 7

Begg's funnel plot for publication bias in meta-analysis of premature birth and breast cancer risk

Begg's funnel plot for publication bias in meta-analysis of premature birth and breast cancer risk. Premature birth (gestational age ≤36 weeks) was compared with gestational age ≥37 weeks. Egger test, P = 0.03; Begg test, P = 0.11. rr, relative risk; s.e., standard error.

We examined 13 studies (eight case-control and five cohort) that assessed the association between twin status and risk (Table 6). Most studies identified a slightly increased risk among twins 15313243455863646566, with five studies demonstrating significant associations 3158646566. In contrast, some studies observed a slightly reduced risk 142067, with one of the risks being marginally significant 67. Seven studies 203258636566 had information on zygosity. Of these studies, two 5863 used the twins' sex as a proxy for zygosity. For monozygotic twins, a reduction in risk was significant in one study 68. Most studies failed to observe an association 203258636566. Three studies reported a significantly increased risk associated with being a dizygotic twin 586566, whereas other studies reported no association 20326367 (Figure 8).

Table 6

Studies assessing the association of twinship with risk for breast cancer

Type of study

Ref.

Year

Design

Cases

Controls (or cohort)

Country/place of study

Category

OR (95% CI)

Comments

Case-control studies

[63]^a

1992

MCC

870

2,741

UK, USA

Singleton

Referent

Adjusted for age, study center, parity, age at first birth, age at menarche, height, body mass index, maternal age at birth, birth order, and menopausal status

Twinship

1.40 (0.77–2.55)

Singleton

Referent

Monozygote twin

1.30 (0.58–2.92)

Dizygote twin

1.54 (0.64–3.71)

[14]

1996

PCC

1,134

1,380

USA

Age 21–45

Adjusted for age, menopausal status, and maternal smoking

Singleton

Referent

Twinship

0.6 (0.3–1.3)

Age 50–64

Singleton

Referent

Twinship

0.9 (0.4–2.2)

[58]^a

1997

PCC

2,150

1,961

USA

Singleton

Referent

Twinship

1.6 (1.0–2.7)

Singleton

Referent

Monozygote twin

1.39 (0.7–2.6)

Dizygote twin

2.06 (1.0–4.5)

[32]

1997

NCC

1,068

2,727

Sweden

Singleton

Referent

Adjusted for maternal age, matermal socioeconomic status, maternal parity, maternal pre-eclampsia or eclampsia, neonatal jaundice, severe prematurity, twin, and birth weight

Twinship

1.3 (0.8–2.1)

Singleton

Referent

Monozygote twin

0.7 (0.2–2.2)

Dizygote twin

1.5 (0.8–2.7)

[15]

2000

LCC

481

2,863

USA

Singleton

Referent

Crude ORs

Twinship

1.04 (0.51–2.11)

[43]

2001

LCC

319

768

USA

Singleton

Referent

Crude ORs

Twinship

1.6 (0.2–10.1)

[45]

2004

LCC

2,522

10,052

USA

Singleton

Referent

Adjusted for age and maternal age at first birth

Twinship

1.77 (1.05–2.97)

[20]

2005

PCC

2,338

2,476

Poland

Singleton

Referent

Adjusted for age, education, age at menarche, menopausal status and age at menopause, age at first full-term pregnancy, number of full-term pregnancy, family history of breast cancer among first-degree relatives, mammography screening, and current body mass index

Twinship

0.76 (0.49–1.16)

Singleton

Referent

Monozygote twin

0.90 (0.53–1.52)

Dizygote twin

0.58 (0.23–1.47)

Cohort studies

[64]

1980

LTCohort

270

(16,922)

Denmark

Twinship

1.1 (1.0–1.2)

Observed/expected ratio (95% CI)

[65]

1995

LTCohort

740

(25,541)

Sweden

Twinship

1.1 (1.0–1.1)

Observed/expected ratio (95% CI)

Monozygote twin

1.0 (0.9–1.2)

Dizygote twin

1.1 (1.0–1.2)

[67]

1999

LTCohort

245

(13,176)

Finland

Twinship

0.91 (0.81–1.00)

Observed/expected ratio (95% CI)

Monozygote twin

0.76 (0.59–0.97)

Dizygote twin

0.98 (0.84–1.10)

[66]

2000

Cohort

1,230

(29,197)

USA

Singleton

Referent

Adjusted for age, education, family history of breast cancer, age at menarche, age at first birth, height, current body mass index, body mass index at age 18, waist:hip ratio, alcohol drinking, and hormone replacement therapy

Twinship

1.72 (1.22–2.42)

Singleton

Referent

Monozygote twin

1.04 (0.43–2.5)

Dizygote twin

1.77 (1.16–2.7)

[31]

2006

Cohort

249

1,024

USA

Singleton

Referent

Adjusted for age at diagnosis, diagnosis year, stage at diagnosis, and birth order, with exception of birth order, which is adjusted for maternal age

Twinship

2.5 (1.0–6.2)

^aAuthors used the female twins as the proxy of the monozygote twin and the female twin with male twin as the proxy of the dizygote twin. Cohort, cohort study; LCC, case-control study with linkage with population and cancer registry data; LTCohort, twin cohort study by using linkage with birth and cancer registry data; MCC, multicenter case-control study; NCC, nested case-control study in cohort; PCC, population-based case-control study.

Figure 8

Meta-analysis for the association between twinship and risk for breast cancer

Meta-analysis for the association between twinship and risk for breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows. Twinship: Q = 18.79 (13 degrees of freedom), P = 0.13; Begg test, P = 0.78; Egger test, P = 0.24. Monozygote twin: Q = 5.79 (6 degrees of freedom), P = 0.45; Begg test, P = 0.55; Egger test, P = 0.85. Dizygote twin: Q = 12.53 (6 degrees of freedom), P = 0.06; Begg test, P = 1.0; Egger test, P = 0.3. ¹The authors used the female twins as the proxy for the monozygote twin and the female twin with male twin as the proxy for the dizygote twin. ²Women aged 21 to 45 years. ³Women aged 50 to 64 years. CI, confidence interval; OR, odds ratio.

The Q test for heterogeneity was not significant (P-Q test = 0.13), and the meta-analysis of 13 studies examining twin status (without regard to zygosity) found an OR of 1.22 (95% CI 1.01 to 1.11). There was no evidence of any publication bias (P-Egger test or P-Begg test >0.1). There were little evidence of heterogeneity (P-Q test > 0.1 for monozygotic or dizygotic twins), and breast cancer risk was not significantly increased among either monozygotic (OR 0.95 [95% CI 0.85 to 1.07]) or dizygotic (OR 1.17 [95% CI 0.99 to 1.37]) twins, albeit based on limited statistical power. In subgroup analysis by study design, cohort studies identified significantly increased risk (OR 1.23 [95% CI 1.00 to 1.11]) for breast cancer in twins versus singletons, with no study heterogeneity (P-Q test = 0.07). Case-control studies showed no association with twin status (OR 1.39 [95% CI 0.91 to 1.12]). There was no evidence of any publication bias (P-Egger test or P-Begg test > 0.05) among the case-control or cohort studies. In subgroup analysis by study design and zygosity, there were no heterogeneity in studies (P-Q test > 0.1). In subgroup analysis by study year, significant heterogeneity by publication year was identified (P = 0.01), and the OR (95% CI) for studies published before 2000 was 1.06 (0.97 to 1.47), whereas the OR (95% CI) for studies published in 2000 or later was 1.27 (1.03 to 1.58).

We identified nine studies that assessed the association between maternal or paternal smoking and risk (Table 7). Two cohort studies reported nonsignificantly reduced risks associated with maternal smoking (OR 0.49 [95% CI 0.29 to 1.03] 68; OR 0.8 [95% CI 0.5 to 1.1] 31), whereas a case-control study 43 identified a significant positive association (age-adjusted OR 2.7 [95% CI 1.1 to 6.3]), although its crude OR was not statistically significant (OR 1.1 [95% CI 0.7 to 1.7]). The majority of studies, however, identified no associations with maternal 142033355869 or paternal 203569 smoking during pregnancy.

There was no heterogeneity or publication bias (P-Q test > 0.05, P-Egger test and P-Begg test > 0.1 among all studies, case-control or cohort). The meta-analysis for maternal smoking (Figure 9) found no significant association with risk (OR 0.98 [95% CI 0.86 to 1.13]), although cohort studies 4068 noted a significant negative association with maternal smoking (OR 0.59 [95% CI 0.41 to 0.85]).

Table 7

Studies assessing the association of maternal or paternal smoking and the risk of breast cancer

Type of study

Ref.

Year

Design

Cases

Controls (or cohort)

Country/place of study

Smoking status

OR (95% CI)

Comments

Case-control studies

[69]

1996

PCC

470

USA

Maternal smoking

Crude ORs

Referent

Yes

0.9 (0.4–2.1)

Paternal smoking

Referent

Yes

1.3 (0.9–1.7)

[14]

1996

PCC

1,086

1,321

USA

Maternal smoking

Adjusted for age, menopausal status, and maternal smoking; OR (95% CI) for maternal smoking among early-onset breast cancer patients (≤ 30 years old) was 1.9 (1.0–3.4)

Age 21–45 years

Referent

Yes

1.1 (0.9–1.3)

Age 50–64 years

Referent

Yes

1.3 (0.9–2.1)

[58]

1997

PCC

522

484

USA

Maternal smoking

Referent

Yes

1.1 (0.8–1.4)

[33]

1998

PCC

507

433

USA

Maternal smoking

Crude ORs

Referent

Yes

1.1 (0.9–1.5)

[43]

2001

LCC

319

768

USA

Maternal smoking

Adjusted for attained age

Referent

Yes

2.7 (1.1–6.3)

[35]^a

2002

PCC

1,535

1,534

USA

Smoking

Adjusted for age and residential regions (states)

Referent

Paternal smoking

1.00 (0.88–1.13)

Maternal/parental smoking

1.10 (0.84–1.42)

[20]

2005

PCC

2380

2,497

Poland

Maternal smoking

Unadjusted; recalculated

Referent

Yes (any exposure)

1.19 (0.97–1.47)

Paternal smoking

Referent

Yes (any exposure)

0.90 (0.77–1.05)

Cohort studies

[31]

2006

Cohort

249

1,024

USA

Maternal smoking

Referent

Adjusted for age at diagnosis, diagnosis year, stage at diagnosis, and birth order, with exception of birth order, which is adjusted for maternal age Crude relative rates

0.8 (0.5–1.1)

Yes (any exposure)

[68]

2005

Cohort

(3,989)

USA

Maternal smoking

Referent

Yes (any exposure)

0.49 (0.29–1.03)

≤ 15 cigarettes a day

0.33 (0.12–0.94)

>15

0.68 (0.26–1.73)

^aTitus-Ernstoff and coworkers [35] classified three categories: nonparental smoking, either paternal or maternal smoking only or both parents smoking during pregnancy. Thus, in this study, the maternal or both parents smoking versus nonparental smoking can be regarded as maternal smoking versus no maternal smoking. Cohort, cohort study; LCC, case-control study by linkage with population data and cancer registry data; PCC, population-based case-control study.

Figure 9

Meta-analysis for the association of maternal smoking during pregnancy with risk for subsequent breast cancer

Meta-analysis for the association of maternal smoking during pregnancy with risk for subsequent breast cancer. The tests for homogeneity and for publication bias in the studies analyzed are as follows: Q = 16.90 (9 degrees of freedom), P = 0.06; Begg test, P = 0.59; Egger test, P = 0.31. ¹Titus-Ernstoff and coworkers [35] classified three categories: nonparental smoking, paternal or maternal smoking only or both parents smoking during pregnancy. The odds ratios (ORs) of father smoking on breast cancer risk was almost unity (OR 1.0, 95% confidence intrval [CI] 0.9 to 1.1). Thus, in this study, the mother smoking and both parents smoking versus nonparental smoking can be considered to the maternal smoking versus no maternal smoking. ²Women aged 21 to 45 years. ³Women aged 50 to 64 years.

Discussion

The main finding of our meta-analysis was that heavier birth weight was associated with increased breast cancer risk (18% increased risk for the heaviest weight). Twin status was associated with 1.2-fold higher risk for breast cancer relative to a singleton birth. Although we found some evidence of increased risk associated with older maternal age (OR 1.16 for maternal age ≥30 years), there were heterogeneous findings across study designs.

Most studies identified an increased risk for breast cancer with heavier birth weight, with the association being particularly strong for premenopausal or early-onset breast cancers 14222930. Our result was similar to the findings of a recent meta-analysis of 26 studies, which revealed that high birth weight was associated with a RR of 1.23 and restricted to premenopausal women (OR 1.25 [95% CI 1.14 to 1.38) 70. This analysis grouped birth weight into two categories (classified into high and low birth weight in each study, regardless of specific weight in terms of grams), preventing evaluation of dose-response relationships. We did in fact observe evidence of a dose-response relationship of risk with birth weight, although this was based on a relatively small number of studies involving three or four categories.

Although some studies identified a J-shaped relationship between birth weight and breast cancer risk 121415182533353745, others failed to note an increased risk associated with very low birth weights. A recent study involving 3,066 breast cancer patients and 106,504 comparison individuals in a Danish cohort also found no elevated risk among those with very low birth weights 71. Similarly, our meta-analysis provided little evidence of increased risk for very low birth weights.

Although the mechanisms underlying the association between high birth weight and breast cancer risk remain unclear, it has been suggested that heavier birth weights may result from increased in utero exposuresto factors such as insulin-like growth factor-I or estrogens 7273747576. These substances may act as mitogens by increasing the likelihood of genetic mutations 7577. However, several studies have failed to find any correlation between umbilical cord estrogen levels and birth weight 7879. One study, however, reported a significant positive relationship with estriol 80. Further studies should be undertaken to assist in the resolution of these conflicting data.

Our analysis found no association of breast cancer risk with birth orders between 2 and 4, but we did note a somewhat reduced risk associated with higher birth orders (at least 5), although the results were heterogeneous across studies. Biologically, pregnancy estrogen levels appear to be higher during first pregnancies and decline in successive pregnancies 81. Furthermore, cord blood levels of estradiol, estrone, and progesterone are lower for later born than first born children 82. These findings suggest that the reduced risk associated with higher birth orders may relate to lower estrogen levels. However, evidence supporting birth order as a risk factor for breast cancer is limited, with further investigations needed to evaluate dose-response relationships more fully.

In our meta-analysis, we found some evidence that having been born to an older mother was associated with higher breast cancer risk, although the results were heterogeneous across studies. Our data failed to support the previous studies that suggested a J-shaped relationship between maternal age and breast cancer risk. It was previously suggested that older maternal age may have an adverse effect on the primordial mammary gland of their daughters because of altered hormonal profiles 37 or may linked to the epigenetic change of mtDNA which can lead to breast carcinogenesis by oocyte inheritance 83. However, the two studies that examined pregnancy estrogen levels according to maternal age found that both total estrogen and estradiol levels were lowest in youngest mothers (<20 years of age), highest in those aged 20 to 24 years, and intermediate in mothers over 25 years of age 7881. Thus, it remains unclear from both our meta-analysis as well as from biologic data whether maternal age is a proxy for estrogen or estradiol exposure to fetus. Although it has been suggested that older paternal age may cause germ cell mutations, previous epidemiologic studies have failed to support an association 352069828485. Because the purpose of this study was to evaluate whether the intrauterine hormone environment affects subsequent breast cancer risk, our meta-analysis did not include paternal age.

We observed no association between prematurity and breast cancer risk. Biologically, women having abruptio placentae or an extremely premature birth (<32 week) have been shown to have elevated levels of human chorionic gonadotropin and α-fetoprotein, which could inhibit the differentiation of stem cells in human breast tissue cells 15. Gestational age is related to birth weight, of course, because birth weights in infants born prematurely are lower than those in infants born at term 13.

Twin pregnancies are associated with an approximate doubling of estrogen levels compared with singleton pregnancies 8687. Dizygotic twin pregnancies have elevated levels of estrogens and gonadotropins 888990. It has therefore been postulated that twins, especially dizygotic twins, could be at an elevated risk for breast cancer. In general, our results did not support differences in risk between monozygotic and dizygotic twins, and there was evidence that risk estimates published after 2000 were qualitatively different from those of earlier studies.

Studies of parental smoking, especially maternal smoking, and daughter's breast cancer risk have yielded inconsistent results. Biologically, maternal smoking, rather than paternal smoking, has a greater impact on the fetus. In the meta-analytic results, both factors failed to exhibit a significant association with risk. Some studies have reported that maternal smoking in pregnancy reduces serum estrogen levels 9192. A recent experimental study reported that both estradiol-17β levels and progesterone:estradiol-17β ratios were reduced in pregnant mice exposed to cigarette smoke 93. However, the relevance of these findings to humans is unclear.

These meta-analyses are based on results from studies involving heterogeneous designs and methodology. We did note between-study heterogeneity for the associations of birth order, maternal age, and twin status. To resolve the heterogeneous findings, we considered the influence of study design and the date of study publication on the results by subgroup analyses. However, heterogeneity in studies could only be explained partially.

Effects of maternal age, birth order, prematurity (cut-off value 32 weeks), and maternal smoking were found to be heterogeneous across study designs, but birth weight and twinning were comparable. Self-reported measures of perinatal factors may be vulnerable to misclassification biases, with differential or nondifferential effects 9495. Because studies based on data linkage to medical records have a lower chance of misclassification bias, we conducted subgroup meta-analyses stratified by source of information (data linkage versus self-report) and found no substantial differences in the results. Although the completeness of records is a critical factor in evaluating biases in studies based on data linkage, most papers did not provide details about the completeness of records. We also conducted subgroup meta-analyses stratified by publication year. Only twin status exhibited significant heterogeneity according to publication year (<2000 versus ≥2000).

Our findings may be somewhat inflated because of our dependence on crude rather than adjusted ORs or RRs. A possible misclassification bias for zygosity might have resulted in studies that used sex as a proxy for zygosity 96. Because this bias would probably attenuate associations, additional investigations are needed to determine the extent of any true association of risk with twin status.

Conclusion

It has been hypothesized that certain perinatal factors, including birth weight and order, twin pregnancies, prematurity, maternal age, and smoking, may reflect higher estrogenic environments in utero, thereby increasing the subsequent risk of breast cancer. Findings of an increase in breast cancer risk among daughters exposed to diethylstilbestrol in utero supports this hypothesis 9798. Although the current meta-analysis found evidence that higher birth weights are associated with increased breast cancer risk, older maternal age and twin status were less convincingly related, and birth order and prematurity appeared unrelated. Greater birth weights have been attributed to higher maternal estrogens levels, which could affect fetal development 727374 through epigenetic modifications of breast stem cells 199100. Although our findings regarding birth weight support the hypothesis that higher estrogen exposures in utero may be involved in the subsequent development of breast cancer, further biologic data are needed to elucidate the relationship fully.

Abbreviations

CI = confidence interval; OR = odds ratio; RR = relative risk.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

SKP collected and selected the all of breast cancer studies, analyzed the data in the study, drafted the manuscript, critically revised the manuscript for important intellectual content, and takes responsibility for the study concept and design, the integrity of the data, and the accuracy of the data analysis. DK participated in design of the study, drafting of the manuscript and interpretation of results, and critically revised the manuscript for important intellectual content. KAM was responsible for the study concept and design, interpreted the findings, and revised the manuscript for important intellectual content. MGC participated in the interpretation of the data and revision of the manuscript. YK was involved in data analysis and revision for important intellectual content. KYY contributed to interpreting the findings and critically revised the manuscript for important intellectual content. LAB led conception and design of the study, the analysis and interpretation of the findings, and revision to the manuscript, and obtained part funding for this research. All authors read and approved the final manuscript.

Acknowledgements

This research was supported, in part, by the Intramural Research Program of the National Institutes of Health (National Cancer Institute).

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