Higher Breast Cancer Risk Among Immigrant Asian American Women Than Among US-Born Asian American Women.

INTRODUCTION: Given rising rates of breast cancer in parts of Asia, immigrant Asian American women in the United States may have higher rates of breast cancer than previously anticipated. This study examined breast cancer risk among Asian American women by nativity and percentage of life lived in the United States, accounting for established breast cancer risk factors. METHODS: We analyzed a breast cancer case-control data set of Asian American women living in the San Francisco Bay Area; this data set included 132 cases of women with breast cancer selected from a Surveillance, Epidemiology, and End Results cancer registry and 438 Asian American women without diagnosed breast cancer matched to cases by age and country of origin. We used logistic regression to compare 3 Asian American groups: US-born, immigrants who lived 50% or more of their life in the United States, and immigrants who lived less than 50% of their life in the United States. RESULTS: In the minimally adjusted and fully adjusted models, both groups of immigrant Asian American women had higher risk of breast cancer than US-born Asian American women. In the fully adjusted model, compared with US-born Asian American women, immigrant Asian American women who lived more than 50% of their life in United States were on average 3 times as likely (odds ratio = 3.00; 95% confidence interval, 1.56-5.75) and immigrants who lived less than 50% of their life in United States were on average 2.46 times as likely (odds ratio = 2.46; 95% confidence interval, 1.21-4.99) to have breast cancer. We found no difference in fully adjusted odds ratios of having breast cancer between the 2 immigrant groups. CONCLUSION: This study provides preliminary evidence that breast cancer risk among immigrant Asian American women may be higher than among their US-born counterparts.

Neighborhood Contexts and Breast Cancer Among Asian American Women.

BACKGROUND: This study examines how neighborhood socioeconomic status (nSES) and ethnic composition are associated with breast cancer risk for Asian American women. METHODS: We linked individual level data from a population-based case-control study of breast cancer among Asian American women with neighborhood level data in the Greater San Francisco Bay Area (cases: n = 118, controls: n = 390). Multivariable logistic regression models examined the association between nSES, ethnic composition, and odds of having breast cancer. RESULTS: Asian American women living in neighborhoods with high nSES and high ethnic composition had the highest odds of breast cancer, compared to those living in neighborhoods with high nSES and low ethnic composition (OR = 0.34, 95% CI [0.16-0.75]) or in neighborhoods with low nSES and high ethnic composition (OR = 0.37, 95% CI [0.17-0.83]). DISCUSSION: Neighborhood socioeconomic and ethnic contexts are associated with breast cancer for Asian American women. We discuss explanations and avenues for future research.

Strategies for recruiting representative samples of Asian Americans for a population-based case-control study.

BACKGROUND: Data are limited on effective methods for recruiting persons, especially from ethnically diverse populations, into population-based studies. The goal of this study was to evaluate the variation among and representativeness of controls identified using multiple methods for a population-based case-control study of breast cancer among Asian Americans, Native Hawaiians and Pacific Islanders (AANHPIs) in the San Francisco Bay Area. METHODS: We used a unique combination of targeted recruitment strategies, including address-based sampling, community-based methods, and internet-based and media-based approaches for recruiting controls, frequency matched on age and ethnicity to a population-based sample of cases. To characterise the participating controls, we compared the distribution of sociodemographic characteristics and cancer risk factors between recruitment sources using χ(2) tests. To ensure that the controls we recruited were representative of the underlying at-risk population, we compared characteristics of the controls, by ethnicity and in aggregate, to data from the California Health Interview Survey (CHIS), and adjusted the relative mix of recruitment strategies throughout the study as needed to achieve representativeness. RESULTS: As expected, controls (n=483) recruited by any single method were not representative. However, when aggregated across methods, controls were largely representative of the underlying source population, as characterised by CHIS, with regard to the characteristics under study, including nativity, education, marital status and body mass index. CONCLUSIONS: A multimode approach using targeted recruitment strategies is an effective and feasible alternative to using a single recruitment method in identifying a representative, diverse control sample for population-based studies.