a Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, 1100 Fairview Avenue North, MP 381, PO Box 19024, Seattle, Washington 981091024, USA.
b School of Public Health and Community Medicine, Department of Epidemiology; University of Washington; Seattle, Washington 98195, USA.
Reprint requests to: Dr Janet R Daling, Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, 1100 Fairview Avenue North, MP 381, PO Box 19024, Seattle, Washington 981091024, USA. E-mail: jdaling{at}cclink.fhcrc.org
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Abstract |
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Methods The participants in this population-based case-control study were postmenopausal women 5064 years of age from the general female population of western Washington State. It included 479 women with incident primary breast cancer and 435 controls.
Results This study found that: (i) women who gained over 70 pounds since age 18 had an increased risk of breast cancer relative to those who stayed within 10 pounds of their weight at age 18 (odds ratio [OR] = 2.7; 95% CI : 1.54.9), (ii) women with body mass indices (BMI) below what is considered healthy had a decreased risk (OR = 0.4; 95% CI : 0.21.1) while women with a BMI in the obese range had an increased risk of breast cancer (OR = 1.4; 95% CI : 1.02.1), and (iii) women who reached their maximum height at or after the age of 18 had a decreased risk of breast cancer compared to women who reached their maximum height at age 13 or younger (OR = 0.7; 95% CI : 0.51.0).
Conclusions By examining various anthropometric variables using clinically relevant strata, a clearer picture of how these variables relate to postmenopausal breast cancer risk was developed. Similar to younger women, postmenopausal women who reached their maximum height at later ages had a decreased risk of breast cancer.
Keywords Breast neoplasms, body weight, body height, body mass index, postmenopausal, United States
Accepted 6 October 1999
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Introduction |
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Specifically, it is hypothesized that a later age at maximum height may decrease a woman's risk of breast cancer and perhaps should be used as a marker to estimate risk, as evidence suggests that this may be true for younger women.21 The biological plausibility of a protective effect of late age at maximum height is based on the influences exposure to growth hormones and insulin-like growth factor during puberty have on breast development. During the growth spurt of puberty, high levels of these hormones contribute to rapid breast growth and may influence the susceptibility of breast tissue to a future malignancy.22 Previous studies have found that the time between age at menarche and age at first live birth is a time of particular risk because of the effects of hormones on the nulliparous breast. So a later age at maximum height may be protective because it reflects a reduction in the time interval between pubertal breast development and the differentiation of breast tissue that occurs at first pregnancy.
Previous studies have primarily assessed BMI in quartiles or quintile groupings, without distinguishing subjects who are too thin or too obese from those in the normal range, making clinical applications of these results difficult. Therefore, in this study, BMI is analysed based on clinically relevant groupings in order to create a better picture of what degree of risk of breast cancer women at different levels of obesity have. Similarly, analyses of weight gain tend to use fairly broad groupings, so in this study narrower categories of weight were used to identify women with the greatest change in risk.
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Materials and Methods |
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Controls were identified from the general population of 5064 year old female residents of King County, Washington through random digit dialling using the Waksberg-Mitofsky method2426 and were frequency matched to cases by 5-year age groups. A total of 545 (73%) of the 747 randomly selected eligible women were interviewed. However, only 435 were used for analysis, since the 57 women who were premenopausal and the 53 women who either had a previous diagnosis of breast cancer or were non-white were excluded.
Women were interviewed in person by trained interviewers who were not blinded to subjects' case-control status. To assist in the subjects' recall, interviewers used a calendar on which major life events were recorded. The questionnaire covered demographic and lifestyle characteristics, medical and reproductive history, and self-reported anthropometric variables. Detailed menstrual, pregnancy, and contraceptive histories were also obtained. Each subject was assigned a reference date and exposures that occurred after this date were not ascertained. This was the date of diagnosis for case patients. Each control was assigned a reference date that approximately matched those of cases on year of diagnosis, and within that year reference months were randomly assigned. With regard to weight, women were asked what their weight was one year prior to the reference date. For all of the recorded variables presented, except for family history of breast cancer, information was missing for eight or fewer subjects who either refused to answer or could not recall answers to the questions posed. These subjects were excluded from the analyses of these variables, and the percentages presented in the tables exclude missing subjects.
The BMI for subjects were calculated based on the heights and weights reported. In the analysis of BMI, women were grouped into clinically relevant categories. In clinical practice, obesity is defined as a BMI >30 kg/m2 and overweight is defined either as >27 kg/m2 or >25 kg/m2.27 Anorexia is defined as those <85% of their ideal body weight or with a BMI <18 kg/m2.28 To approximate these clinical groupings, the BMI data were divided into those <18.1 kg/m2, 18.121.0 kg/m2, 21.125.0 kg/m2, 25.130.0 kg/m2, and >30.1 kg/m2.
Unconditional logistic regression analysis was performed. Using SPSS 8.0 for Windows (SPSS Inc., Chicago IL) statistical software, odds ratios (OR) and 95% CI were calculated to estimate the relative risk of breast cancer for the various factors analysed.29 All analyses presented were adjusted for age as a continuous term in the model. The variables of primary interest, those relating to height and weight, were adjusted for potential confounders in addition to age. Adjustment for the following variables was also performed, and if they did not substantially change the OR or our interpretations of the results (at the = 0.05 significance level) they were left out of the final models: weight, BMI, parity, number of live births, age at first live birth, income, education, marital status, type of menopause, and alcohol, tobacco, oral contraceptive, and hormone replacement therapy use.
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Results |
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Discussion |
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The fact that self-reported measures were used is another potential problem since this may have resulted in some misclassification. This is particularly true for the information on the age when maximum height was attained and age at menarche, as some women may have had to recall events that occurred over 50 years ago. The assumption made however, was that the cases and controls would not differ markedly in the accuracy of their reported anthropometric measurements. In addition, this problem was minimized by the trained interviewers who administered the questionnaires in person and used a life events calendar to enhance recall. In order to aid in participants' recall of the age when they reached their maximum height and what their weight was at age 18, subjects were often asked to remember, for example, when they stopped changing their clothing sizes or what their dress size was at different ages. Further, it is likely that any misclassification problems with these variables would be non-differential and hence lead to OR that are underestimations as such misclassification tends to drive the OR toward the null value.
Another limitation of this investigation is the very narrow age range studied (i.e. 15 years). Most previous studies included a broader age range, and the risks associated with many of the factors studied here are known to change with age. Specifically, it has been shown that the association between BMI and breast cancer risk in postmenopausal women is stronger as age increases.4,17,30
It has not been definitively determined whether height is a risk factor for breast cancer in older women. While this study will not put an end to this issue, its findings support the notion that height is not associated with an increased risk of breast cancer in middle-aged women. Further, by making a comparison not performed in these other studies, between those women at the highest and lowest extremes of height with those in between, perhaps a more clinically relevant assessment of height is made. This is because it was found that women who were either shorter or taller than average did not have a risk of breast cancer that differed to any significant degree from those of more average heights.
Determining the mechanisms through which total height attained influences breast cancer risk is challenging because several factors, including genetics, nutrition, diet, and hormone levels all influence height. However, consistent with a finding in younger women,21 this study found that the age when maximum height is attained might be an important facet of the height variable to consider when assessing breast cancer risk. The rationale behind why this age may be an important predictor of breast cancer risk involves a consideration of the influence growth hormone and insulin-like growth factor (IGF1) have on breast development.21 Growth hormone is involved in the growth spurt and is involved in the regulation of IGF1, which stimulates the growth of breast tissue.31,32 These two events, the onset of the growth spurt and the beginning of breast development, are known to occur together.33 It is postulated that the time between puberty and a woman's first live birth is a time when the breast is particularly susceptible to hormonally or chemically induced carcinogenesis due to the rapid rate of cell replication that occurs during this time.34 Some work has suggested that the time period of importance is between age at menarche and first live birth. This is because oestrogens increase the degree of breast tissue proliferation, which again makes it susceptible to chemical carcinogens up until the time of first live birth.35 However our data suggest that similar to age at menarche, age at maximum height may also be a useful proxy for the onset of the critical and interrelated events associated with pubertal breast development.
How weight and BMI relate to breast cancer risk is an equally complex topic, and there are numerous studies that both support and reject the notion that increased weight or BMI increases risk. Part of the problem may be in the manner in which the data were analysed. The typical methodology found in the literature involves the use of quartiles or quintiles of weight and BMI. One problem with this categorization is that women who are either too thin or too obese to be considered healthy end up in a large group of women most of who are either much heavier or much lighter than they are. If the extreme weights are what influence a woman's risk of breast cancer, such risks cannot be determined if women are grouped in quartiles. When examined in quartiles, the data from this study, similar to other studies, suggest that women who are in the lowest quartile of weight have a reduced risk of breast cancer compared to women of greater weights, and that women in the highest BMI quartile have an elevated risk relative to women in the lowest BMI quartile. However, when the women at different extremes of weight are considered separately and when women in different clinically relevant BMI are compared, a clearer picture is developed. Analysed this way, the data suggest that women who weigh less and may be anorexic (based on a BMI <18.1 kg/m2 ) have a decreased risk of breast cancer relative to women with more average weights or normal BMI, though this could have been due to chance. On the other hand, it was found that women who were heavier and had a BMI that put them in the most obese category had an elevated risk.
One explanation for these observations relating to weight and BMI is the role that adipose tissue plays in oestrogen production and circulation with the onset of menopause. At this time adipose tissue is the primary oestrogen producer and simultaneously levels of triacylglycerol and insulin rise. The combination of these factors is believed to increase the length of a woman's exposure to oestrogen and to make the oestrogen that she is exposed to more active.22,36 Therefore, through this hormonal mechanism one may expect more obese women to be at a greater risk for breast cancer because they have an excess of adipose tissue, whereas women who are too thin have very little of such tissue possibly explaining their observed decreased risk. Further, anorexia can also suppress reproductive hormones which can lead to an overall lower lifetime exposure to oestrogen among such women.
The final result to consider is a woman's change in weight from age 18 to her weight one year prior to the reference date. Few studies have closely examined this variable, but the evidence that weight gain influences breast cancer risk is compelling, with several recent studies confirming this result.16,18,19 Again though, the tendency in these studies was to consider only a few large categories of weight change, typically tertiles or quartiles, with the group who gained the most defined as having gained more than 40 to 45 pounds. Two recent studies, however, did consider smaller increments of weight gain similar to this study.5,37 The highest weight group in these studies included women who gained >25.0 kg (>55 lbs) and the calculated relative risks for these women were 1.41 and 1.57. Our results are consistent with these findings showing a markedly elevated risk of breast cancer in women who gained over 70 pounds (rather than >55 lbs) since age 18 (OR = 2.7; 95% CI : 1.54.9). Of note, the risk estimates for the other strata of weight gain did not vary much from the reference group. Thus, the results suggest that women who gained 31 to 70 pounds, who previous studies have found to be at an increased risk of breast cancer, may not in fact have such an increased risk. A physiological explanation for why weight gain may effect risk breast cancer risk comes from a consideration of the influence adipose tissue and menopause exerts on the potency and levels of oestrogen as described above. However, the timing of the weight gain was not known among the study subjects and this may also be an important facet of this exposure. For example, weight gain confined to the postmenopausal period may exert different effects than weight gained at younger ages.
This study examined breast cancer risk associated with various anthropometric measures both using the ways they have traditionally been investigated in the literature and using some novel approaches in categorizing them in an effort to better characterize how these variables may function to influence risk. The factors we found to affect risk were age at maximum height, the time between age at maximum height and age at first live birth, weight and BMI, and weight gain. The relationships between these various anthropometric variables were elucidated through a consideration of related factors and biological interactions as well as through the division of the data into smaller and more clinically relevant strata. Further use of such analytical techniques is encouraged to further and hopefully more accurately elucidate the roles of these variables in predicting breast cancer risk.
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Acknowledgments |
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References |
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