Abstract
Background.
Breast cancer is the most common cancer in women. Asian American women have experienced steadily increasing breast cancer incidence rates over the past several decades. The increased rate might be in part due to acculturation.
Methods.
We tested the hypothesis that higher level of acculturation was associated with higher mammographic breast density (MBD), an indicator of breast cancer risk, in a cohort of 425 premenopausal Chinese immigrant women in Philadelphia. Generalized estimating equations accounted for repeated observations and adjusted for age, type of mammographic image, body mass index, months of breastfeeding, number of live births, age at first birth, and menopausal stage (pre, early peri, late peri, post).
Results.
Results indicated that acculturation level was not associated with any of the MBD measures.
Conclusion.
Findings were contrary to our hypothesis and previous, cross-sectional studies. In this study population, reproductive factors had a greater effect on MBD than acculturation-related behaviors in adulthood.
Keywords: breast cancer, acculturation, immigrants, mammographic breast density, Asian
INTRODUCTION
Breast cancer is the most common cancer in women, regardless of race or ethnicity (1). Although most racial and ethnic groups in the United States (U.S.) experienced stable or declining breast cancer incidence rates over the past several decades (2, 3), rates in Asian and Asian American women have steadily increased (1–6). The increase in Asian women is especially pronounced among younger cohorts, with some studies showing higher incidence rates among premenopausal women (7) or women <50 years (5, 6). Reasons for the increase are unknown, but acculturation, or the adoption of the behaviors and values of the mainstream culture (8, 9), is often thought to contribute to the increase in risk among foreign-born women who have migrated to the U.S. The literature on acculturation and breast cancer risk indicates that more acculturated women, whether assessed in terms of generational status, length of U.S. residence, language use or more detailed questionnaires on cultural orientation, have higher breast cancer risk than less acculturated women (8, 10–13).
Percent breast density, the proportion of the total area of the breast that appears radiographically dense, is a well-established marker of breast cancer risk (14–18). Because mammographic dense tissue is composed chiefly of epithelial and stromal cells, and tumors may arise as a result of the proliferation of epithelial cells and their interaction with stromal extracellular matrix (19, 20), dense tissue area is thought to be a more etiologically relevant marker of risk (21). Confirming an association between level of acculturation and breast density could help explain the increase in breast cancer risk in young Asian American women. To our knowledge, only three studies (8, 22, 23) have explored the issue, with inconsistent results.
The current study explored whether level of acculturation was associated with mammographic breast density (MBD) in a sample of U.S. Chinese immigrant women. We hypothesized that women reporting a higher level of acculturation would have higher MBD. We specifically expected acculturation to be associated with area of MBD, but we also examined percent density because of its strong link to breast cancer.
METHODS
Study Sample
Between October 2005 and April 2008, a convenience sample of 436 pre- or perimenopausal women was recruited into a study of MBD and acculturation through local community organizations and word of mouth throughout Philadelphia. The study was designed to capture the peri-menopausal period or the time just preceding it, as a window when breast density is thought to change more rapidly (24, 25). Eligibility criteria included Chinese heritage, migration from Asia ≤20 years ago, and being of mammography screening age (≥35 y). Exclusion criteria at baseline were: postmenopausal status (no menstruation in the past year); history of breast augmentation/reduction, prophylactic mastectomy, or any cancer except nonmelanoma skin cancer; current pregnancy; current breastfeeding or breastfeeding within last 9 months; or symptoms of new breast problem, such as palpable lump, skin changes, or nipple discharge. Participants were contacted each year for follow-up of mammographic and other measures. Follow-up ended in April 2010, with each participant having one to four visits during the study. Participants received $20 as reimbursement for their time at each visit. The study was reviewed and approved by the Fox Chase Cancer Center Institutional Review Board.
Data Collection
At each data collection visit, trained bilingual and bicultural interviewers conducted structured, detailed, language-appropriate health interviews that elicited information on sociodemographic characteristics; health behaviors; acculturation; reproductive history, including pregnancies, and oral contraceptive or other hormone use; family history of breast cancer; breastfeeding duration; weight, height, and waist circumference; and smoking. Baseline interviews also requested information on country of birth, education level, marital status, and age at menarche. Based on information from each visit, women were classified as premenopausal if they reported menses in the last 3 months with no decrease in predictability, early perimenopausal if they reported menses in the last 3 months but with decreased predictability, or late perimenopausal if they reported 3–11 months of amenorrhea (26, 27).
Mammographic Breast Density
Mammograms were conducted at Fox Chase Cancer Center or on its mobile mammography unit, at no cost to study participants. For most participants at baseline, cranio-caudal mammographic views were digitized using a Kodak LS-85 laser film scanner at a resolution of 100 pixels/cm. Beginning in April of 2007, Fox Chase Cancer Center began a transition to digital mammography equipment and digital images became directly available, eliminating the need to scan and digitize images. Of the images included in this analysis, just over half (52%) were digital images taken directly by digital mammography. Of note, a previous study found that mode of image acquisition (film-screen or digital mammography) produced no difference in radiologist-assigned breast density category (28).
All mammograms were assessed by one observer in batches of about 60 images using Cumulus, a highly reproducible computer-assisted method (29, 30) to calculate dense breast tissue area (cm2), non-dense area (cm2; total breast area minus dense area), and percent density (dense area over total breast area). One side was randomly selected for assessment of breast density for each participant. Serial images for the same participant were included in the same batch but assessed in random order (31). Each batch also included duplicate images from four randomly selected participants to evaluate intra-and inter-batch reproducibility. Intra- and inter-batch correlation coefficients based on duplicate readings were all ≥0.92 (range 0.92–0.99), indicating excellent reproducibility.
Acculturation
Level of acculturation was measured using an abridged version of the General Ethnicity Questionnaire – American version (GEQA) (32).The GEQA was chosen because of its demonstrated validity as a measure of cultural orientation among Chinese immigrants in the U.S. (32, 33). Items in the scale were translated into Chinese, translated back into English, discussed and further revised by the research team, then pilot-tested among a sample of middle-aged Chinese immigrant women. The questionnaire’s eleven items assessed exposure (“Now, I am exposed to American culture,” “I go to places where people are American”), familiarity (“I am familiar with American cultural practices and customs”), and extent of integration into American culture (“I engage in American forms of recreation,” “I celebrate American holidays,” “At home, I eat American food,” “At restaurants, I eat American food,” “Now, my friends are American,” “I listen to American music,” “How much do you speak English at home?”), as well as feelings towards the culture and its people (“I admire people who are American”). Most responses were on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), except for one question on English language use that was graded from 1 (not at all) to 5 (very much). Responses were averaged across items, resulting in a minimum score of 1.0 (least acculturated) and a possible maximum score of 5.0 (most acculturated). The scale demonstrated high construct validity and internal reliability (Cronbach’s alpha=.91) in the study sample (34, 35).
Statistical Analyses
Of the 436 women enrolled in the study, three women did not complete the baseline questionnaire, seven had no mammographic images, and one was missing data on number of live births. The analysis therefore includes 425 women, who contributed a total of 1,102 observations over the course of the study. Of these women, 115 provided information at only one timepoint (no follow-up). Among the 310 participants (73%) who provided information on at least two visits, 111 provided data on three occasions, and 133 provided data on four, over a mean (SD) length of follow-up of 2.6 (0.9) years. One woman who did not contribute a mammogram at baseline but contributed later mammograms after becoming post-menopausal was retained in the analysis.
In bivariate analyses using baseline data, we categorized GEQA scores into quintiles, with the lowest quintile representing the least acculturated group of women and the highest quintile representing the most acculturated. We used ANOVA to compare distributions of continuous covariates across levels of acculturation, and Cochran-Mantel-Haenszel chi-square test statistics to examine associations with categorical covariates. Covariates were identified as potential confounders if they were associated (p<0.10) with at least one of the mammographic measures.
We conducted preliminary analyses to determine whether acculturation was longitudinally associated with breast density among women with >1 data collection visit. Models with change in breast density measures as the primary outcome variables and either baseline or change in acculturation score as the primary predictor showed no significant associations. However, as reported previously (35), the magnitude of change in acculturation scores was relatively small over the follow-up period. Moreover, statistical power to estimate change in breast density over the follow-up was reduced by the transition from film to digital mammography partway through the study, which produced more variable estimates of breast tissue area. Consequently, our analyses instead used generalized estimating equations (GEE) to take into account repeated measures, with an exchangeable correlation matrix.
GEQA was modeled in multivariate linear regression models as both a continuous variable and in quintiles. All models were minimally adjusted for age (continuous years) and type of mammographic image (film or digital). Next, we used a backward selection procedure to determine the set of variables to retain in final models by including all covariates identified as potential confounders in bivariate analyses, then systematically removing covariates from the model one at a time based on their level of significance as a predictor in the model. If removing the variable changed the parameter estimate for continuous GEQA score by ≥10% for the parameter estimate or if the variable remained a (p<0.10) predictor of at least one of the three outcome variables, it was retained in the model. Final models adjusted for age, type of mammographic image, months of breastfeeding (0–<6 months, 6–<12 months, 12–<36 months, ≥36 months), a combined variable representing number of live births and age at first live birth (≥3 livebirths and age at first live birth 15–<25 years; 2 livebirths and age at first live birth 15–<25 years; 0–1 livebirth and age at first live birth 15–<25 years; ≥3 livebirths and age at first live birth 25–<45 years; 2 livebirths and age at first live birth 25–<45 years; 0–1 livebirth and age at first live birth 25–<45 years), and menopausal stage (pre-, early peri-, late peri-, post-menopausal). Because BMI might act as both a confounder and a mediator of the association between acculturation and breast density, we present results from models with adjustment for BMI separately. Other variables evaluated as possible confounders but not included in final models, following the procedure described above, were age at migration, length of U.S. residence, country of birth, level of education, marital status, age at menarche, family history of breast cancer, and ever use of oral contraceptives or other female hormones. All variables were time-dependent except for country of birth, education level, marital status, and age at menarche, for which we used information reported at baseline. P-values for trend across GEQA quintiles were estimated by modeling GEQA quintiles as an ordinal variable.
Modeling GEQA as a continuous variable and in quintiles produced similar results. Here we present results based on GEQA modeled as quintiles for ease of interpretation. All analyses were conducted using SAS (version 9.4, 2013, SAS Institute, Cary, NC).
RESULTS
Among the 425 women in the sample, mean (SD) age was 43.9 (4.5) years (range 35–56 years) (Table 1). Almost all women (97%) were born in China, with the remaining 3% born in Hong Kong, Singapore, Cambodia, Vietnam, Malaysia, or Burma. The women had lived in the U.S. for a mean (SD) of 7.5 (4.8) years (range <1–21 years) and had a mean (SD) age at migration of 36.4 (6.4) years (range 16–54 years). Almost all (93%) were married, and half (49%) had up to 8 years of education. Mean (SD) GEQA score was 2.1 (0.7) for the overall sample; this varied from 1.1 (0.1) in the least acculturated group to 3.2 (0.3) in the most acculturated group. Compared to less acculturated women, women with higher acculturation scores were significantly more likely to have some college education and less likely to be married or born in China (Table 1). More acculturated women reported a younger age at menarche, fewer live births, higher age at first live birth, and less breastfeeding. Additionally, at the last visit, 34 women reported being post-menopausal (not shown).
Table 1.
Descriptive characteristics at baseline for all participants and by quintiles of acculturation score, among 425 Chinese immigrant women in the [removed for blinding] region.
| All women | Quintiles of Acculturation Scores | ||||||
|---|---|---|---|---|---|---|---|
| Variables | (n=425) | 1 (n=85) | 2 (n=81) | 3 (n=67) | 4 (n=96) | 5 (n=96) | P-value1 |
| Mean (SD) age (years) | 43.9 (4.5) | 43.8 | 44.2 | 43.7 | 43.8 | 43.9 | 0.97 |
| Born in China (%) | 97.2 | 99.0 | 99.0 | 98.5 | 98.8 | 90.6 | 0.002 |
| Mean (SD) age at Migration (years) | 36.4 (6.4) | 37.1 | 37.2 | 36.5 | 36.1 | 34.9 | 0.13 |
| Mean (SD) length of U.S. residence (years) | 7.5 (4.8) | 6.8 | 6.7 | 7.2 | 8.1 | 8.9 | 0.008 |
| Married (%) | 92.5 | 99.0 | 94.8 | 97.0 | 88.9 | 82.3 | 0.0002 |
| Education (%) | |||||||
| 0 to 8 years | 48.5 | 63.5 | 61.5 | 49.2 | 45.7 | 18.8 | <.0001 |
| High School/Technical School | 34.8 | 35.4 | 35.4 | 41.8 | 29.6 | 32.9 | |
| Some college or higher | 16.7 | 1.0 | 3.1 | 9.0 | 24.7 | 48.2 | |
| Mean (SD) General Ethnicity Questionnaire score | 2.1 (0.7) | 1.1 | 1.8 | 2.1 | 2.5 | 3.2 | <.0001 |
| BMI, kg/m2 | 23.5 (2.8) | 23.6 | 23.7 | 23.3 | 23.0 | 23.6 | 0.41 |
| Age of menarche2 (years) | 14.8 (1.7) | 15.3 | 15.0 | 15.1 | 14.8 | 14.1 | <.0001 |
| Number of livebirths | 2.0 (1.0) | 2.4 | 2.0 | 2.1 | 1.8 | 1.5 | <.0001 |
| Age at first live birth2, years | 25.2 (4.6) | 23.1 | 24.5 | 24.5 | 26.4 | 28.2 | <.0001 |
| Breastfeeding (%) | |||||||
| 0–<6 months | 33.6 | 21.9 | 29.2 | 26.9 | 46.9 | 44.7 | |
| 6–<12 months | 29.6 | 28.1 | 32.3 | 26.9 | 24.7 | 35.3 | 0.0005 |
| 12–<36 months | 23.3 | 27.1 | 25.0 | 35.8 | 18.5 | 11.8 | |
| >=36 months | 13.4 | 22.9 | 13.5 | 10.4 | 9.9 | 8.2 | |
| Menopausal stage (%) | |||||||
| Pre | 68.2 | 59.4 | 69.8 | 67.2 | 71.6 | 74.1 | 0.2239 |
| Early peri | 22.1 | 30.2 | 25.0 | 17.9 | 18.5 | 16.5 | |
| Late peri | 9.4 | 10.4 | 5.2 | 14.9 | 9.9 | 8.2 | |
| Post | 0.2 | 0 | 0 | 0 | 0 | 1.2 | |
| Ever used contraceptives/hormones (%) | 14.3 | 12.5 | 7.3 | 17.9 | 16.0 | 20.0 | 0.1243 |
| Breast cancer family history (%) | 1.2 | 0 | 1.0 | 0 | 2.5 | 2.3 | 0.3898 |
| Mean (SD) area of dense tissue (cm2) | 36.1 (16.4) | 34.2 | 38.5 | 36.2 | 33.3 | 38.1 | 0.1399 |
| Mean (SD) area of non-dense tissue (cm2) | 44.4 (22.5) | 49.5 | 42.2 | 38.9 | 45.9 | 44.1 | 0.0344 |
| Mean (SD) percent density | 46.1 (15.8) | 42.1 | 49.1 | 49.4 | 43.4 | 47.2 | 0.0041 |
p-values from ANOVA comparing means of continuous covariates or from Cochran-Mantel-Haenszel chi-square test statistics comparing distributions of categorical covariates across quintiles of acculturation score
Values were missing for age at menarche (n=1), and age at first live birth (n=12).
In models adjusted for age and type of mammographic image, each one-unit increase in BMI (kg/m2) was associated with a 0.38 cm2 increase in dense tissue area (p=0.09), a 3.80 cm2 increase in non-dense tissue area (p<0.0001), and a 1.45 percentage point decrease in percent density (p<0.0001) (Table 2). Older age at first live birth and fewer live births were associated with lower non-dense tissue area (p=0.003) and positively associated with percent density (p<0.0001); compared to women with ≥3 live births and age at first live birth <25 years, women with 0–1 live birth and age at live birth ≥25 years had −11.94 cm2 smaller non-dense tissue area and percent density that was 8.74 percentage points higher. Longer breastfeeding history was associated with greater non-dense tissue area (p=0.002) and inversely associated with percent density (p=0.001); compared to women who had breastfed for <6 months, women who had breastfed for ≥36 months had 15.12 cm2 more non-dense tissue area and percent density that was 7.88 percentage points lower. Dense tissue area was >2 cm2 less in late peri- and post-menopausal women compared to pre-menopausal women (p=0.06).
Table 2.
Covariate associations with breast density measures from multivariate linear regression models1 based on 1,102 observations from 425 Chinese immigrant women in the [removed for blinding] region.
| Beta2 (p-value) | |||
|---|---|---|---|
| Variables | Dense area | Non-dense area | Percent density |
| Age (years) | −0.27 (0.06) | 1.64 (<0.0001) | −0.90 (<0.0001) |
| Not born vs. born in China | −3.38 (0.32) | −5.81 (0.32) | 0.68 (0.83) |
| Age at Migration (years) | −0.10 (0.53) | −0.24 (0.21) | 0.04 (0.78) |
| Length of U.S. residence (years) | 0.10 (0.53) | 0.24 (0.22) | −0.03 (0.79) |
| Unmarried vs. married | −1.69 (0.63) | 2.86 (0.55) | −1.59 (0.48) |
| Education | (0.89) | (0.12) | (0.56) |
| 0 to 8 years (ref) | 0 | 0 | 0 |
| High School/Technical School | −0.76 | −4.57 | 1.21 |
| Some college or higher | −0.31 | −3.81 | 1.60 |
| BMI (kg/m2) | 0.38 (0.09) | 3.80 (<0.0001) | −1.45 (<0.0001) |
| Age at menarche (years) | −0.32 (0.43) | 0.23 (0.71) | −0.34 (0.34) |
| Age at first live birth / # livebirths | (0.39) | (0.003) | (<0.0001) |
| >15–<25 / ≥3 livebirths (ref) | 0 | 0 | 0 |
| >15–<25 / 2 livebirths | 2.95 | −3.31 | 4.01 |
| >15–<25 / 0 or 1 livebirth | 1.81 | −9.08 | 6.00 |
| 25–<45 / ≥3 livebirths | 1.13 | 2.84 | 0.73 |
| 25–<45 / 2 livebirths | 3.97 | −8.25 | 7.00 |
| 25–<45 / 0 or 1 livebirth | 5.14 | −11.94 | 8.74 |
| Breastfeeding | (0.47) | (0.002) | (0.001) |
| 0–<6 months (ref) | 0 | 0 | 0 |
| 6–<12 months | 2.33 | 0.50 | 1.02 |
| 12–<36 months | −1.04 | 3.20 | −1.50 |
| >=36 months | −0.76 | 15.12 | −7.88 |
| Menopausal stage | (0.063) | (0.86) | (0.25) |
| Premenopausal (ref) | 0 | 0 | 0 |
| Early perimenopausal | −0.28 | 0.05 | −0.22 |
| Late perimenopausal | −2.68 | 1.60 | −1.82 |
| Postmenopausal | −2.20 | 1.19 | −1.93 |
| Ever vs. never used contraceptives/hormones | 0.70 (0.72) | 2.41 (0.39) | −0.93 (0.58) |
| Breast cancer family history, yes vs. no | −2.85 (0.58) | 1.08 (0.84) | −1.93 (0.73) |
All models included age and type of mammographic image.
Beta represents cm2 change in dense or nondense area or absolute 1% change in percent density per unit increment for continuous variables. For categorical variables, beta represents cm2 change in dense or nondense area or absolute 1% change in percent density for given category relative to referent category.
Level of acculturation was not significantly associated with dense tissue area in minimally or fully adjusted models (Table 3). In minimally adjusted models, non-dense tissue area was consistently lower for women in the upper four quintiles for acculturation compared with women in the lowest quintile (p<0.10), but associations were attenuated after adjustment for number of live births / age at first live birth, breastfeeding duration, and menopausal status. Similarly, the minimally adjusted model showed a suggestive inverse association between acculturation and percent density; women in the highest quintile for acculturation had 2.23 percentage points higher percent breast density than women in the lowest quintile (p=0.03), with a suggestive trend (p=0.07). But the difference was small and also attenuated after adjusting for reproductive factors. Notably, additional adjustment for BMI did not substantially change estimates except in the model for non-dense tissue area.
Table 3.
Associations of quintiles of acculturation score with mammographic measures based on 1,102 observations from 425 Chinese immigrant women in the [removed for blinding] region.
| Beta1 (p-value) by quintile of acculturation score | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | Trend p2 | |
| Dense area | ||||||
| Minimally adjusted3 | 1.0 | −0.13 (0.88) | −.01 (0.99) | 0.32 (0.73) | 1.13 (0.28) | 0.30 |
| Fully adjusted4 | 1.0 | −0.19 (0.81) | −0.07 (0.94) | 0.17 (0.85) | 0.76 (0.48) | 0.49 |
| + BMI5 | 1.0 | −0.23 (0.77) | −0.08 (0.93) | 0.16 (0.86) | 0.78 (0.46) | 0.47 |
| Non-dense area | ||||||
| Minimally adjusted | 1.0 | −2.08 (0.08) | −2.59 (0.05) | −2.64 (0.07) | −2.67 (0.08) | 0.07 |
| Fully adjusted | 1.0 | −1.81 (0.12) | −2.38 (0.07) | −2.0 (0.16) | −1.35 (0.38) | 0.29 |
| + BMI | 1.0 | −2.26 (0.06) | −2.69 (0.04) | −2.26 (0.11) | −1.09 (0.47) | 0.37 |
| Percent density | ||||||
| Minimally adjusted | 1.0 | 1.41 (0.09) | 1.72 (0.41) | 1.20 (0.18) | 2.23 (0.03) | 0.07 |
| Fully adjusted | 1.0 | 1.19 (0.15) | 1.34 (0.11) | 0.59 (0.50) | 1.14 (0.28) | 0.46 |
| + BMI | 1.0 | 1.32 (0.11) | 1.45 (0.08) | 0.68 (0.44) | 1.06 (0.32) | 0.49 |
Beta represents cm2 difference in dense or nondense area or absolute 1% difference in percent density in given quintile relative to lowest quintile of acculturation score.
Trend p estimated by fitting model with quintiles of acculturation score as ordinal variable.
Includes age (continuous years) and type of mammographic image (film or digital)
Includes age (continuous years); type of mammographic image (film or digital); months of breastfeeding (0–<6 months, 6–<12 months, 12–<36 months, ≥36 months); number of live births and age at first live birth (≥3 livebirths and age at first live birth 15–<25 years; 2 livebirths and age at first live birth 15–<25 years; 0–1 livebirth and age at first live birth 15–<25 years; ≥3 livebirths and age at first live birth 25–<45 years; 2 livebirths and age at first live birth 25–<45 years; 0–1 livebirth and age at first live birth 25–<45 years); menopausal stage (pre-, early peri-, late peri-, post-menopausal)
Fully adjusted model + BMI
DISCUSSION
In this sample of Chinese immigrant women, we observed a suggestive association of acculturation with higher percent density, but no significant association with dense tissue area. The association between acculturation and percent density was attenuated with adjustment for reproductive factors, suggesting that the association may be explained by existing, pre-migration differences in reproductive characteristics across levels of acculturation.
A study of roughly 200 Chinese immigrant women in Philadelphia found a strong, significant association between level of acculturation, measured based on English proficiency and ethnicity of neighbors, friends, and coworkers, and breast density, assessed using ordinal Breast Imaging Reporting and Data System (BIRADS) categories (22). Similarly, in a sample of 477 women in New York City (NYC), monolingual Spanish women had significantly lower percent density (−5.83%) than monolingual English women (8). In contrast, in Chinese and Japanese participants in the Study of Women’s Health Across the Nation (SWAN), low acculturation assessed based on language preference was associated with larger dense tissue area and higher percent density compared with those who were born in the U.S. or had high acculturation scores, in models adjusting for age and BMI (23).
The strong associations between acculturation and breast density in the Philadelphia (22) and NYC (8) studies might be due to greater variability in acculturation in their study samples, especially as ours was a generally low-acculturation sample of Chinese immigrants. Indeed, the NYC study included White and Black women in addition to U.S.-born as well as foreign-born Hispanic women, and most of the difference in percent density appeared to be between foreign-born and U.S.-born Hispanic women (8). Taken together, these findings suggest that effects of ‘acculturation’ may not be detectable over a short time frame or even within a single generation, but might instead be apparent only across generations or cross-sectionally across different populations; this is also consistent with our prior observation that participants reported relatively little change in acculturation over a brief (<4 year) follow-up period (22).
In addition, the Philadelphia and NYC studies (8, 22) included post-menopausal women, whereas the SWAN study (23) did not, and the current study sample was predominantly pre-menopausal. If the effects of acculturation on MBD and breast cancer risk are mediated by effects on lobular involution associated with menopause, then these effects might be more apparent only after menopause.
Overall, studies on acculturation and breast density provide little support, if any, for an association with dense tissue area, and only partial support for an association with percent density. Dense tissue area is thought to increase risk because of the greater proliferative potential of epithelial cells (21). In this study, the association of acculturation with percent density was due more to differences in non-dense tissue area than in dense tissue area. Whether non-dense tissue area is also of etiologic relevance merits further exploration (36, 37).
Moreover, it may be that reproductive or other factors established before or immediately after migration have a greater effect on MBD and breast cancer risk, such that risk trajectories were established earlier than the assessments conducted for this study. A greater orientation towards western culture early in life, for example, could be associated with earlier menses, and if immigration was for education or work, it is also possible that by immigrating, these women changed their reproductive trajectories by delaying reproduction more so than if they had remained in their country of origin. Reproduction-related factors such as earlier menses, later age at first birth, and fewer children may result in longer breast tissue exposure to estrogen, increasing breast density (38) as well as breast cancer risk (39). Thus, it could be that the effects of acculturation on MBD are mostly mediated by reproductive factors. Nevertheless, as the first study of acculturation and MBD to include repeated assessments, our analysis examines key factors that have been proposed to alter risk trajectories after migration. Future studies might expand upon this work by comparing the experiences of immigrants undergoing more or less rapid changes in acculturation– for example, depending on their residence in an immigrant enclave by assessing possible differences in risk trajectory by sociocultural context.
A limitation of our study is the short follow-up time; a longer follow-up with a greater number of visits might have captured more change and variability in MBD. Another limitation is the potential lack of generalizability of our sample of Chinese immigrant women. The generally low acculturation level of women in the sample may also have limited our ability to observe any differences across groups. However, given that U.S. Census Bureau often combine all Asian Americans without considering the variety of experiences and differential levels of risk within this heterogeneous demographic group (2), information on specific subpopulations can provide unique insight. Our findings shed light on an understudied population of young immigrant Chinese women, now known to be experiencing rising rates of breast cancer for which we have no clear explanation (2, 4).
A significant strength of the study was the use of a valid and reliable computer-assisted method to accurately assess MBD. Additionally, with a sample size of 425 women, this is the largest of the existing studies on acculturation and MBD in foreign-born women in the U.S.
Acculturation has long been assumed to contribute to increased breast cancer risk among U.S. Asians. The present study suggests that if acculturation does increase breast cancer risk it might be due to effects of reproductive factors on MBD. Moreover, this study adds to a growing body of research suggesting that our prior expectations regarding acculturation and cancer risk may be incorrect. Emerging evidence suggests that breast cancer incidence in foreign-born Asian women in the U.S. may now be higher than that of U.S.-born Asian Americans (7), possibly rendering the concept of the post-migration acculturation process irrelevant, at least with respect to predicting breast cancer risk. Acculturation may be more likely to be associated with breast cancer stage at diagnosis and prognosis via pathways involving access to screening and care (40–43). In terms of risk, however, more important might be to identify the factors, both pre- and post-migration, that can be modified to counter the now increasing incidence of breast cancer in Asian American women. Such research should include a larger and more diverse sample to represent a broader range of experiences, exposures, and risk; distinguish among the different Asian American populations given their different experiences and levels of risk; and be longitudinal in design to capture changes in breast cancer risk and risk factors.
ACKNOWLEDGEMENTS
The authors thank Ms. Wanzi Yang, Ms. Qi He, Ms. Rong Cheng, Ms. Bingqin Zheng, Ms. Zemin Liu and Ms. Yun Song for their crucial work in collecting and managing data for the study; the Fox Chase Cancer Center Population Studies Facility for its data management support; and Dr. Philip Siu and Dr. Thomas Yuen of Chinatown Medical Services, and Dr. Ari Brooks and Ms. Sriya Krishnamoorthy of the Drexel University College of Medicine for their generous assistance in participant recruitment and provision of care.
Funding: This study was funded by the Doris A. Howell Foundation-CSUPERB Research Scholars Program, the Cal Poly Office of University Diversity & Inclusion, The Louis Stokes Alliance for Minority Participation in STEM at Cal Poly, the National Science Foundation Grant HRD-1826490, and the National Institutes of Health Grant R01 CA106606.
Footnotes
Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.
Disclaimer: The views expressed are those of the author(s) and do not necessarily reflect the official views of the Uniformed Services University of the Health Sciences or the Department of Defense.
Conflict of Interest: The authors declare that they have no conflict of interest.
Contributor Information
Rebeca Almeida, Department of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA.
Carolyn Y. Fang, Fox Chase Cancer Center, Philadelphia, PA.
Celia Byrne, Uniformed Services University of the Health Sciences, Bethesda, MD.
Marilyn Tseng, Department of Kinesiology and Public Health, California Polytechnic State University, San Luis Obispo, CA.
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