Explaining the Relation Between Education and Postmenopausal Breast Cancer

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1 American Journal of Epidemiology Copyright O 1997 by The Johns Hopkins University School of Hygiene and Public Health All rtght3 reserved Vol. 145, No. 4 Printed in U.S.A Explaining the Relation Between Education and Postmenopausal Breast Cancer Katherine E. Heck and Elsie R. Pamuk The authors examined the relation between socioeconomic status, as defined by education level, and postmenopausal breast cancer incidence using data from the National Health and Nutrition Examination Survey I Epidemiologic Followup Study. Female participants in the study were followed from to Cox proportional hazards modeling was used to determine the relation between breast cancer incidence and education level. There was a direct dose-response association between education level and postmenopausal breast cancer risk. Several breast cancer risk factors, including height and reproductiverelated risks such as nulliparity, were found to mediate this relation. Adjustment for these factors reduced, but did not eliminate, the positive relation between education level and risk of postmenopausal breast cancer; however, the association was no longer statistically significant. The association between higher education and increased risk of breast cancer appears to be largely explained by differences in the known risk factors for breast cancer. Am J Epidemiol 1997; 145: breast neoplasms; education; socioeconomic factors Unlike most other illnesses, breast cancer has been associated with higher socioeconomic status. This correlation has appeared at both the individual and the community level. Case-control studies in the United States, Canada, and Israel (1, 2) indicate that women with more than years of education have a significantly increased risk of breast cancer. In a Canadian study (3), education was not related to breast cancer risk, but cases tended to have greater family incomes than controls. A number of ecologic analyses of US data (4-9) have found higher rates of breast cancer incidence and mortality among women living in more affluent communities. Smaller, individual-level studies (10-15) have suggested the same disparity. Research in countries as diverse as Brazil (16), Finland (17-19), Italy (20), Denmark (21), and Australia (22) have found positive relations between breast cancer incidence and socioeconomic status. Although most research suggests this link between higher socioeconomic status and breast cancer, few US studies have been able to examine nationally representative individual-level data or to control for mediating variables. The first National Health and Nutri- Received for publication April, 1996, and accepted for publication October 9, Abbreviations: NHANES I, first National Health and Nutrition Examination Survey; NHEFS, NHANES I Epidemiologic Followup Study. From the National Center for Health Statistics, Hyattsville, MD. Reprint requests to Katherine E. Heck, National Center for Health Statistics, 6525 Belcrest Road, Room 730, Hyattsville, MD tion Examination Survey (NHANES I) Epidemiologic Followup Survey (NHEFS) has been used to examine multiple risk factors for breast cancer because it provides an opportunity to use individual-level data to examine the incidence of breast cancer among a nationally representative cohort of several thousand women, followed for up to 22 years, and to examine the effects of known breast cancer risk factors as well as socioeconomic variables. In one study using NHEFS, Carter et al. (23) found that education past high school was associated with a greater risk of breast cancer. Another socioeconomic variable, income, also has been positively associated with breast cancer risk in NHEFS (24). Additional examination of the link between breast cancer and socioeconomic status may provide more information about the etiology of the disease and why breast cancer risk appears to increase with higher socioeconomic status. Determining the extent to which the unusual association between breast cancer and socioeconomic status is explained by known risk factors should provide more specific information about which women are at high risk of acquiring the disease. MATERIALS AND METHODS The research question to be addressed by this analysis was whether socioeconomic status is related to the incidence of breast cancer and whether such a relation could be explained by variation in reproductive and 366

2 Education and Postmenopausal Breast Cancer 367 other breast cancer risk factors, which may vary between women of different socioeconomic standing. The NHEFS data include several indicators of socioeconomic status, such as education, income, poverty level of the census tract, and urban/rural status. However, many women in the sample were older than retirement age, when income and other social circumstances can change rapidly. Education was chosen to represent socioeconomic status because it is a more constant measure of lifelong social status than variables such as income or residence. The sample available for this study consisted of all women (n = 8,596) who took part in the NHANES I Epidemiologic Followup Study (25). NHANES I, a survey and physical examination focusing on nutrition status and other health issues, was conducted during on a national probability sample of the noninstitutionalized population of the United States. The NHEFS sample consisted of all NHANES I participants who were years of age at the original survey. NHEFS participants were tracked and subsequently surveyed in three periods, , 1987, and Participants older than 55 years at baseline were also surveyed in The NHEFS collected health and demographic information through an interview of the subject or a proxy, obtained death certificates for participants who had died, and requested medical records from hospitals in which the subject or proxy reported an overnight stay during the follow-up period. The response rate to the full NHANES I (survey and medical examination) was 69.5 percent. Of the original sample, 93 percent were traced by the wave, and 87 percent were either interviewed or a proxy was interviewed, with a loss to follow-up of 3.5 percent between and the follow-up survey. The study population excluded female participants who were not traced (n = 376), women of a race other than black or white (n = 87; race in NHANES I was collected by interviewer observation, and no ethnicity information was collected), women with missing information on education level (n = 51), and women identified as having breast cancer prevalent at baseline (n = 56). Staff of the National Cancer Institute completed a medical record review of breast cancer cases in NHEFS in August This study used the National Cancer Institute designations of case status and date of diagnosis. Case ascertainment and determination of diagnosis date was made from a thorough review of available medical records, self-reports, and death certificates. For the eight cases for whom ascertainment was made only through the death certificate, a date of diagnosis was imputed based on age-specific survival rates from the Surveillance, Epidemiology, and End Results (SEER) cancer surveillance program. There were too few premenopausal cases to examine separately, so this analysis was limited to postmenopausal breast cancer. Women who never reached menopause during the follow-up period or who had an incidence of premenopausal breast cancer were excluded (n = 1,669), as were 96 additional women for whom data were missing for the variables of interest. The final sample consisted of 229 cases and 6,032 noncases. The relative risk of breast cancer incidence at four levels of education by years of completion (<,,, or sl6) was estimated using Cox proportional hazards modeling in SUDAAN (26). Effects were calculated as age-adjusted relative risks with 95 percent confidence intervals. The dependent variable was time to incidence of breast cancer. Because the outcome being evaluated was postmenopausal breast cancer, only postmenopausal follow-up time was included in the model. Thus, all follow-up time was included for women who were postmenopausal at baseline, and women who went through menopause during the follow-up period contributed only the postmenopause portion of their follow-up time. Time was counted as days between menopause or baseline and diagnosis date of breast cancer for cases, or between menopause or baseline and last date known alive (usually last interview date or date of death) for noncases. All models controlled for age at baseline, entered as a continuous variable. The sample originally was stratified on race, since both breast cancer risk factors and education level differed among white and black women. Overall, however, the results were similar; so the two were combined in the final analyses. The following variables were examined as possible mediators of the education-breast cancer relation: nulliparity/age (in years) at first birth (nulliparous, age 30 or older at first birth, age 25-29, age 20-24, or teenage mother); age (in years) at menarche (<13, ^13); age (in years) at menopause ( 45, >45; using date of oophorectomy if earlier than or in lieu of natural menopause and using a value of 5 if otherwise missing, based on a study of average age at natural menopause (27)); any alcohol use in the months before baseline; height in quintiles; body mass index (weight/height 2 ) in quintiles; having a first degree family history of breast cancer; ever having taken oral contraceptives; ever having taken hormone or estrogen replacement therapy; and family income in the year before baseline, in approximate quartiles (<$7,000, $7,000-9,999, $10,000-14,999, >$ 15,000). Age at first birth was not measured during the initial examination but was asked of respondents and proxies

3 368 Heck and Pamuk in each wave beginning in This variable was imputed for 750 women who said at baseline that they had had a birth, but for whom age was missing from follow-up data; these women were assigned educationand age-specific first birth values. Other variables were measured at baseline, except for parity, age at menopause, oral contraceptive use, and hormone replacement therapy use, which were also asked in the follow-up surveys; later values were used for missing data in the first wave. Bivariate models were used to estimate the associations between breast cancer and each potentially mediating variable. A multivariate model was then calculated to examine the relative risk associated with level of education, controlling for other risk factors. The mediating variables were added to the model in the following order: first, race and family history of breast cancer; then the reproductive-related variables of nulliparity/age at first birth, age at menarche, and age at menopause. Hormone use (ever having taken oral contraceptives, ever having taken hormone replacement therapy) was added, followed by alcohol use, then body mass index, and then height. Finally, income was added to the model to examine whether it explained the remaining socioeconomic variability in breast cancer risk. RESULTS The association between the variables of interest and the women's educauon levels was calculated for the study population (table 1). Higher education was associated with postmenopausal breast cancer. Educated women had fewer births and were older at their first birth than women with fewer years of education. They were more likely to have ever taken oral contraceptives and hormone replacement therapy. More educated women were more likely to have had at least one drink of alcohol in the past year than were less educated women. A plurality of women had years of education; 45.1 percent of the weighted sample had more than a TABLE 1. Characteristics* by education level of female partidpants in the National Health and Nutrition Examination Survey I Epidemiologic Followup Study, Characteristic Breast cancer cases (%) Mean age at baseline (years) White race (%) Family history of brea3t cancer Mean age at first birth (years) Mean no. of births Mean age at menarche (years) Mean age at menopause (years) Ever took oral contraceptives Ever took hormone replacement therapy Any alcohol use Body mass index quintiles (kg/m 2 ) (%)t > <20.91 Height quintiles (cm) (%) > <156.3 Income (%)f <$7,000 $7,000-9,999 $10,000-14,999 $15,000 < (n» 3,604) Education level (years) (n = 3,080) * VEilues are weighted percentages or means of each educational group, t Percentages may not total 100 due to rounding. (n = 962) :16 (n = 814)

4 Education and Postmenopausal Breast Cancer 369 high school education. When we controlled for age, education level at baseline was a strong predictor of breast cancer incidence in the NHEFS sample during the follow-up period (table 2). There was a strong and direct dose-response relation between years of education and postmenopausal breast cancer risk. Certain reproductive factors were related to breast cancer. Women who were nulliparous and those who were older at menopause tended to have a slightly higher risk of breast cancer. Age at menarche had a somewhat negative association with breast cancer; TABLE 2. Bivariate age-adjusted associations with postmenopausal breast career risk among black and white female participants in the National Health and Nutrition Examination Survey I Epidemlologic Followup Study, Variable < White race (compared with black) Family history of breast cancer Nulliparity/age at first birth (years) Nulliparous First birth at age 30 First birth at age First birth at age First birth at age <20 Age at menarche <13 years Age at menopause >45 years Ever took oral contraceptives Ever took hormone/estrogen therapy Any alcohol use Body mass index (kg/m 2 ) > <20.91 Height (cm) > <156.3 Income $15,000 $10,000-14,999 $7,000-9,999 <$7,000 Relative risk* 2.3 f t f t 0.9 I.Of 95% confidence Interval * Relative risk of having an occurrence of postmenopausal breast cancer. All models control for age at baseline, t Reference group. however, this variable was missing for many women, some of whose menses began decades before baseline. Postmenopausal hormone use and oral contraceptive use were not significantly associated with breast cancer. Women with a family history of breast cancer had a slightly increased risk of the disease. Body mass index was unrelated to breast cancer risk, but height had a strong association. The tallest women in this sample had a risk of breast cancer three times that of the shortest women. The association between education and breast cancer decreased to nonsignificance but did not disappear when we controlled for the various breast cancer risk factors (table 3). Adding the reproductive risk factors to the model decreased the relative risk. The variables with the greatest effect in decreasing the relative risk were the reproductive risks, including nulliparity, and height. The final multivariate model continued to demonstrate a slight positive association between postmenopausal breast cancer incidence and education level during the follow-up period; however, this difference was no longer statistically significant. The addition of income to the model did not further explain the socioeconomic disparity in postmenopausal breast cancer risk (table 4). Income did not have the same dose-response relation to breast cancer that education had; only women at the highest level of income were at greater risk for breast cancer. DISCUSSION We hypothesized that higher education level would be associated with a greater incidence of breast cancer but that the association among more educated women might be explained by other factors such as nulliparity, being older at first birth, and greater use of synthetic hormones. The hypothesis that higher education would be associated with breast cancer incidence was confirmed, and the association was largely explained by the addition of known breast cancer risk factors to the model. After adjustment for differences in nulliparity/ age at first birth, height, menarche and menopause, and other risk factors for breast cancer, the effect of higher education on breast cancer incidence was substantially reduced and no longer statistically significant. The addition of income to the multivariate model did not reduce the association between education and breast cancer. This suggests that factors other than income per se are more likely to contribute to the etiology of postmenopausal breast cancer, or that income was not well measured by the baseline evaluation. A single measure of household income may not adequately reflect average lifetime financial resources,

5 370 Heck and Pamuk TABLE 3. Multlvariate age-adjusted models of postmenopausal breast cancer risk among black and white female participants In the National Health and Nutrition Examination Survey I Epldemiologlc Followup Study, Variable Relative risk* 95% confidence interval Model 1: Education + race + family history of breast cancer < Model 2: Model 1 + nulliparity/age at first birth + age at menarche + age at menopause < t Model 3: Model 2 + oral contraceptive use + hormone replacement Model 4: Model 3 + alcohol use + body mass + Model 5: Model 4 + height * Relative risk of having an occurrence of postmenopausal breast cancer. Models 1-5 control for age at baseline. Each model adds progressively more variables without eliminating prior ones. + Reference group. particularly among a group so varied in age at baseline. A similar association with income has been found in earlier studies using this data set (23, 24). Certain breast cancer risk factors could not be examined in this analysis due to inadequate data. Breastfeeding information was not sufficient for analysis, nor was access to health care information available. However, many women were older than 65 years during most or all of the study period, so Medicare may have reduced the effect of differential access to care due to socioeconomic status. Certain reproductive variables, such as abortion history and first pregnancy outcome, were also not available for examination. The associations previously delineated between breast cancer and various risk factors tended to be borne out in this study. For example, being childless, having a family history of breast cancer, and being tall were all found to be associated with a higher risk of breast cancer, replicating previous research. The lower breast cancer risk among women in this study whose first birth occurred after age 30 may be an artefact of the small number of women in this category among this older cohort. Certain associations that we found to be weak have generated mixed results in previous studies, and these include the association with hormone replacement therapy (28-32), oral contraceptives (32-36), and body mass index (37-41), often associated with premenopausal but not postmenopausal breast cancer (1, 42). The association between moderate alcohol consumption and breast cancer is disputed in the literature (43-45). In an earlier study that used this data set of the association between alcohol use and risk of breast cancer, Schatzkin et al. (46) found a slightly increased risk among postmenopausal alcohol users (relative risk = ). In this sample, which included a longer follow-up period and more cases, drinking was not associated with breast cancer. However, the simple baseline measure of any drinking in the months before baseline rather than a more comprehensive lifetime assessment of alcohol intake may have been too insensitive to provide an accurate estimate of the breast cancer risk associated with alcohol use. Using the NHEFS data set, Madigan et al. (24) found a greater relative risk of breast cancer (relative TABLE 4. Multivarlate fully adjusted models* of postmenopausal breast cancer risk, by Income and education level, among black and white female participants in the National Health and Nutrition Examination Survey I Epldemlologic Followup Study, variable < Income $15,000 $10,000-14,999 $7,000-9,999 <$7,000 Relative risk* % confidence Interval Relative risk of having an occurrence of postmenopausal breast cancer. The models above control for age at baseline, education, Income, race, family history of breast cancer, nulliparity/age at first birth, age at menarche, age at menopause, oral contraceptive use, hormone replacement therapy, alcohol use, body mass index, and height + Reference group.

6 Education and Postmenopausal Breast Cancer 371 risk = ) associated with family history of breast cancer than was found in this study. Previous results of NHEFS studies may be expected to vary somewhat due to the longer follow-up time and the more complete case ascertainment used here. In addition, family history of breast cancer is associated with earlier and more aggressive disease, so the longer follow-up time will tend to reduce the relation. That higher education in itself should be a risk factor for breast cancer seems unlikely. The biologic factors hypothesized to mediate this relation, such as nulliparity or an older age at first birth among more highly educated women, did not fully explain the excess risk among the most highly educated group, although the residual risk attributed to this group was no longer statistically significant. Variability in the reproductive histories of older women in this sample may not have been measured well enough to exhibit the expected differential; misclassification of some variables, such as menarche, may have blunted their effects. Other unmeasured factors, such as breastfeeding, diet, use of therapeutic abortion, exposure to environmental toxins, or access to diagnostic services, might further explain the variation in this data set. The mixed age of this cohort may have reduced the magnitude of the socioeconomic effect on breast cancer. The meaning of education may have changed over time: A college education was less common in earlier decades, so a given education group may represent a mix of socioeconomic categories, related to age. Women in the cohort who were younger than 65 years might appear to have variability in incidence because those with access to care could have cancer diagnosed earlier, whereas among older women in the cohort, the ascertainment-related variability would be reduced because Medicare diminishes socioeconomic differences in access to care. In addition, the breast cancer differential by social class may have diminished over time. A Finnish incidence study (18) found greater social class variability in breast cancer among women born before Finally, abortion may be related to breast cancer risk. One researcher (47) has suggested that abortion was more common among higher socioeconomic status women before 1973, whereas in more recent years, poorer and younger women are more likely to obtain abortions. Thus, the socioeconomic effect on breast cancer may have been blunted by combining women of different age groups. This study provided new information about the relation between postmenopausal breast cancer incidence and socioeconomic status. The results confirm the findings of several analyses that breast cancer is related to higher socioeconomic status and, in particular, a higher education level. That highly educated women are at greater risk is partially explained by their tendency to have no children, to be older at menopause, and to be tall. Simultaneously controlling for several known breast cancer risk factors reduced the elevation in risk among well-educated women to nonsignificance. This study helps to confirm that the higher breast cancer risk seen among well-educated women appears to be attributable to these women's greater exposure to breast cancer risk factors. ACKNOWLEDGMENTS The authors thank Dr. Rachel Ballard-Barbash for her assistance with the case definitions for this study and Dr. Nancy Krieger for her helpful comments on an earlier version of this manuscript. REFERENCES 1. 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