Environment and Breast Cancer: Science Review
About
Birth characteristics and subsequent risk for breast cancer in very young women
Innes, K., Byers, T., Schymura, M. Am J Epidemiol. 2000. 152:12, 1121-8.
Topic area
Early life exposures
Early life exposures
Study design
Population based case-control
Population based case-control
Funding agency
NCI
NCI
Study Participants
Number of Cases
484
484
Number of Controls
Controls: 2870
Controls: 2870
Participant selection: Inclusion and exclusion criteria
Criteria used to select participants in the study.
In: Cases: All women who were diagnosed with breast cancer in New-York state between 1978 and 1995 and who were also born in New-York state after 1957 and for whom matching with birth record was available.
Controls: the next six liveborn females whose mothers resided in the same county at the time of delivery and who were not subsequently diagnosed with breast or endometrial cancer in New York state.
Ex: controls who died during the first 12 months of life
Comment about participation selection
No follow-up of controls after 12 months of life
No follow-up of controls after 12 months of life
Exposures investigated
Birthweight, gestational age, preeclampsia, multifetal gestation, maternal age at subject's birth, paternal age
Birthweight, gestational age, preeclampsia, multifetal gestation, maternal age at subject's birth, paternal age
How exposure was measured
Other: Birth records
Other: Birth records
Statistical Analysis
Breast cancer outcome investigated
Primary incident breast cancer
Primary incident breast cancer
Ethnic groups with separate analysis
If this study provided a separate analysis by ethnic or racial group, the groups are listed here.
White, African American, other
Confounders considered
Other breast cancer risk factors, such as family history, age at first birth, and hormone replacement therapy use, that were taken into account in the study.
BMI, parity, alcohol consumption, family history of breast cancer
Genetic characterization included
If the study analyzed relationships between environmental factors and inherited genetic variations, this field will be marked “Yes.” “No”, if not.
No
Description of major analysis
Conditional logistic regression conditioned on maternal country of residence, age, and birth date, and additionally adjusted for other intrauterine exposures. Adjusted OR with 95% CI; birthweight >= 4500g versus 2500-3499g; gestational age: <33 versus >=
Conditional logistic regression conditioned on maternal country of residence, age, and birth date, and additionally adjusted for other intrauterine exposures. Adjusted OR with 95% CI; birthweight >= 4500g versus 2500-3499g; gestational age: <33 versus >=
Strength of associations reported
Birthweight: 3.10 (1.18-7.97); gestational age: 0.11 (0.16-0.79); preeclampsia: 0.90 (0.36-2.27); multifetal gestation: 1.04 (0.51-2.11); maternal age: 1.94 (1.18-3.18); paternal age: 1.52 (1.03-2.23)
Birthweight: 3.10 (1.18-7.97); gestational age: 0.11 (0.16-0.79); preeclampsia: 0.90 (0.36-2.27); multifetal gestation: 1.04 (0.51-2.11); maternal age: 1.94 (1.18-3.18); paternal age: 1.52 (1.03-2.23)
Results Comments
The results suggest a J-shapped relation between a woman's own birth weight and her subsequent risk of developing breast cancer and that high birth weight carries an especially pronounced increase in risk. Severe prematurity appeared to reduce subsequent risk for very early onset breast cancer. There was a finding of a rising breast cancer risk with parental age.
The results suggest a J-shapped relation between a woman's own birth weight and her subsequent risk of developing breast cancer and that high birth weight carries an especially pronounced increase in risk. Severe prematurity appeared to reduce subsequent risk for very early onset breast cancer. There was a finding of a rising breast cancer risk with parental age.
Author address
Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver 80262, USA. Kim.Innes@UCHSC.edu
Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver 80262, USA. Kim.Innes@UCHSC.edu
Controls participation rate
Not reported
Not reported