Table 1.
Article # | Primary Author/Year | Study design | Sample size | Study population | Age range | Study purpose | Type of SDOH | SDOH category based on HP 2030 | Association between SDOH and Outcome (Significant/non-significant)* | Type of methodology/Analysis used |
---|---|---|---|---|---|---|---|---|---|---|
1 | Agenor et al. (2020) | Cross-sectional study | n = 45,031 | National Health Interview Survey Female Respondents | 40–75 years old | To examine odds in receiving a mammogram in relationship to sexual orientation across racial/ethnic groups | Race/Ethnicity | Social and community context | Significant | Adjusted Wald tests, Logistic regression |
Sexual orientation | Social and community context | Significant | ||||||||
2 | Agrawal et al. (2021) | Cross-sectional study | n = 919 | African American church going women from Houston, Texas | 40–86 years old | To examine factors associated with adherence to the National Comprehensive Cancer Network breast cancer screening guidelines | Race/Ethnicity | Social and community context | Significant | T-test, Chi-square, Logistic regression |
3 | Alabdullatif et al. (2022) | Cross-sectional study | n = 94,290 | National Health Interview Survey female respondents | ≥40 years old | To examine the association between IT based health care communication and mammography utilization as modified by race/ethnicity/age | Race/Ethnicity | Social and community context | Significant | Logistic regression, Trend analysis |
Age | ||||||||||
4 | Alatrash et al. (2021) | Cross-sectional study | n = 316 | Muslim and Christian Arab American Women from Jordan, Lebanon, and Egypt | ≥40 years old | To examine associations of sociodemographic characteristics with perceived benefits and barriers to mammogram screening | Race/Ethnicity | Social and community context | Significant | Fishers exact test, Bonferroni post hoc test, Chi-square test, and OR test |
5 | Anderson et al. (2014) | Cross-sectional study | n = 138 | Central cancer registry data linked to Medicare claims from three Appalachian states (Pennsylvania, Ohio, and Kentucky) | ≥65 years old | To examine the relationship of an area-based measure of breast cancer screening and geographic area deprivation on the incidence of later stage breast cancer across a diverse region of Appalachia | Economic status | Economic stability | Significant | Exploratory spatial data analysis, multivariate regression, and linear regression |
Insurance status | Health care access and quality | Significant | ||||||||
6 | Asgary et al. (2014) | Cross-sectional study | n = 100 | Homeless women that received services at Barbara Kleinman Shelter in Brooklyn and Bowery Residence Committee’s Safe Haven at least three times between 2010 and 2012 | 50–74 years old | To evaluate and compare rates and predictors of mammograms in homeless and low-income domicile patients | Income | Economic stability | Non-significant | T-test, Multivariable logistic regression |
Insurance status | Health care access and quality | Non-significant | ||||||||
Housing | Neighborhood and built environment | Non-significant | ||||||||
Race | Social and community context | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
Access to provider counseling | Health care access and quality | Significant | ||||||||
History of mental illness | Social and community context | Non-significant | ||||||||
Substance/alcohol abuse | Social and community context | Non-significant | ||||||||
HIV status | Social and community context | Non-significant | ||||||||
7 | Ayanian et al. (2013) | Cross-sectional study | n = 577,316 | Medicaid beneficiaries in 2009 | 65–69 years old | To examine use of mammography in relation to race/ethnicity in Medicare health maintenance organizations, PPO, and traditional Medicare | Income | Economic stability | Significant | Logistic regression |
Insurance status | Health care access and quality | Significant | ||||||||
Race/Ethnicity | Social and community context | Significant | ||||||||
Area of residence | Neighborhood and built environment | Significant | ||||||||
8 | Balazy et al. (2019) | Retrospective Cohort study | n = 1,057 | Single institution women undergoing breast radiotherapy from 2012 to 2017 | 56–60 years old | To examine whether non-English speaking patients present at a later stage than their respective English-speaking counterparts and whether language is associated with mammographic screening | Language | Social and community context | Significant | Ordinal logistic regression, Trend analysis |
Race/Ethnicity | Social and community context | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
9 | Beaber et al. (2016) | Cohort study | n = 3,413 | Women from Geisel School of Medicine and Brigham and Women’s Hospital primary care networks from 2011 to 2013 | ≥40 years old | To evaluate factors influencing when women begin screening after turning 40 years of age within a network of primary care practices | Race/Ethnicity | Social and community context | Non-significant | Kaplan–Meier cumulative incidence, Cox proportional hazards regression |
Access to healthcare providers | Health care access and quality | Significant | ||||||||
Health insurance | Health care access and quality | Significant | ||||||||
Household income | Economic stability | Significant | ||||||||
Zip code | Neighborhood and built environment | Significant | ||||||||
10 | Beaber et al. (2019) | Cohort study | n = 51,241 | 10 PROSPR sites with women receiving first mammograms in 2011 | 50–74 years old | To evaluate multilevel predictors of non-adherence among screened women | Age | Social and community context | Significant | Logistic regression, Multivariable analysis |
Race/Ethnicity | Social and community context | Significant | ||||||||
Zip code | Neighborhood and built environment | Non-significant | ||||||||
Median income | Economic stability | Non-significant | ||||||||
11 | Calo et al. (2016) | Cross-sectional study | n = 1,541 | Participants of 2010 Houston Survey and contextual data from United States Census | 40–74 years old | To evaluate associations between area level socioeconomic measures and mammography screening among a racially and ethnically diverse sample of women in Texas | Age | Social and community context | Significant | Chi-square test, Two level random intercept regression model, Bivariate analysis, and Multivariable analyses |
Insurance | Health care access and quality | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Race/Ethnicity | Social and community context | Significant | ||||||||
Housing | Neighborhood and built environment | Significant | ||||||||
12 | Castaneda et al. (2014) | Cross-sectional study | n = 208 | Survey through UCSD health system | ≥40 years old | To examine factors associated with mammography screening utilization among middle-aged Latinas | Age | Social and community context | Significant | Exploratory factor analysis, Logistic regression |
Income | Economic stability | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Language | Social and community context | Significant | ||||||||
Race/Ethnicity | Social and community context | Significant | ||||||||
13 | Cataneo et al. (2022) | Cross-sectional study | n = 22,825 | LEP and English-speaking female participants who filled the NHIS survey in 2015 | 40–75 years old | To evaluate the impact of limited language proficiency in screening for breast cancer | Language | Social and community context | Significant | Linear regression, Chi-square test, and Stepwise multivariate regression analysis |
Income | Economic stability | Significant | ||||||||
Insurance | Health care access and quality | Significant | ||||||||
Access to primary care providers | Health care access and quality | Significant | ||||||||
Race/Ethnicity | Social and community context | Significant | ||||||||
14 | Chandak et al. (2019) | Retrospective cross-sectional study | n = 7,673 | Women diagnosed with breast cancer between 2008 and 2012 as noted in the Nebraska Cancer Registry | 40–70 years old | To examine rural–urban differences in access to breast cancer screening in a predominantly rural Midwestern state in the United States | Geographic location | Neighborhood and community context | Significant | Spatial analysis, Hot spot analysis |
Access to mammography facilities | Health care access and quality | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
15 | Christensen et al. (2023) | Retrospective cross-sectional study | n = 457,476 | 5% sample of American Indian and White women receiving Medicare fee-for-service in AZ, CA, NY, MX, OK, and WA | 40–89 years old | To examine the impact of urbanicity and income on receiving mammography for American Indian women compared with that for White women | Race | Social and community context | Significant | Multivariable logistic regression analysis, Linear regression |
Income | Economic stability | Significant | ||||||||
Neighborhood | Neighborhood and built environment | Significant | ||||||||
16 | Clark et al. (2017) | Cohort study | n = 48,234 | Women who received digital breast tomosynthesis (DBT) from 22 primary care centers in the Dartmouth-Brigham and Women’s Hospital Population-based Research Optimizing Screening through Personalized Regimens research center (PROSPR) | 49–65 years old | To examine DBT trends and estimated associations with insurance type | Insurance type | Health care access and quality | Significant | Descriptive statistics, Repeated measures analysis using generalized estimating equations (GEE) |
Zip code | Neighborhood and built environment | Non-significant | ||||||||
Race | Social and community context | Non-significant | ||||||||
Neighborhood household income | Neighborhood and built environment/Economic stability | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
17 | Clarke et al. (2019) | Cross-sectional study | n = 29,951 | Women who participated in the 2005, 2008, 2010, 2013, and 2015 National Health Interview Survey | 50–74 years old | To present national estimates of mammography screening among women by nativity, birthplace, and percentage of lifetime living in the United States (U.S.) | Birthplace | Neighborhood and built environment | Non-significant | Descriptive Statistics, Two-sided t tests |
Citizenship | Social and community context | Non-significant | ||||||||
Length of time in the United States | Social and community context | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
Race/Ethnicity | Social and community context | Non-significant | ||||||||
Educational attainment | Education access and quality | Non-significant | ||||||||
Poverty status | Economic stability | Non-significant | ||||||||
Health insurance | Health Care Access and Quality | Non-Significant | ||||||||
18 | Davis et al. (2017) | Cross-sectional study | n = 758 | Patients presenting to radiology department for routine screening mammography from December 2016 to February 2017 | > 40 years old | To clarify why late screening might occur in an at-risk population | Race/Ethnicity | Social and community context | Significant | Descriptive statistics, Univariate logistic regression, and Multivariate logistic regression |
Age | Social and community context | Significant | ||||||||
Employment status | Economic stability | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
Insurance status | Health care access and quality | Significant | ||||||||
Access to mammography | Health care access and quality | Significant | ||||||||
Education level | Education access and quality | Significant | ||||||||
19 | Dong et al. (2022) | Case–control study | n = 33,537 | Patients diagnosed with invasive breast cancer from the Ohio Cancer Incidence Surveillance System between 2010 and 2017 | 40–64 years old | To examine whether there were reductions in geospatial disparities in advanced stage breast cancer at diagnosis in Ohio after Medicaid expansion | Area of residence | Neighborhood and built environment | Significant | Space–time scan statistic in SaTScan |
Household income | Economic stability | Significant | ||||||||
Medicaid coverage | Health care access and quality | Significant | ||||||||
Education level | Education access and quality | Significant | ||||||||
Household vehicle availability | Economic stability/Social and community context | Significant | ||||||||
Insurance coverage | Health care access and quality | Significant | ||||||||
20 | Duggan et al. (2019) | Cross-sectional study | n = 240 | Residents of two adjacent rural counties in Lower Yakima Valley in eastern Washington state who self-identify as Latina or Non-Latina white | ≥40 years old | To examine county-level difference, stratified by ethnicity, of predictor of breast-screening utilization in rural underserved communities | Race/Ethnicity | Social and community context | Non-significant | Multivariate logistic regression |
Education level | Education access and quality | Significant | ||||||||
Income | Economic stability | Non-significant | ||||||||
County of residence | Neighborhood and built environment | Significant | ||||||||
Access to clinic | Health care access and quality | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
21 | Elkin et al. (2014) | Cross-sectional study | n = 1,749 | Adult women attending mammography facilities certified by the FDA under the Mammography Quality Standards Act (MQSA) in six states in 2011 | ≥ 40 | To survey certified mammography facilities in CA, CT, GA, IA, NM, and NY regarding wait times for next available screening, availability of evening and weekend appointments and digital mammography, and insurance copayment requirements | Access to mammography facilities | Health care access and quality | Significant | Chi-square tests |
Insurance copayments | Health care access and quality | Significant | ||||||||
22 | Fedewa et al. (2016) | Cross-sectional study | n = 18,459 | Women aged ≥40 years from the 2008 and 2013 National Health Interview Surveys | ≥ 40 years old | To examine changes in nationwide mammography prevalence and physician recommendation among younger (≥ 40) and older (≥ 75) women by insurance and SES before and after the 2009 USPSTF BC screening guidelines | Insurance status | Health care access and quality | Significant (for younger women) | Chi-square tests, Logistic regression models |
Income | Economic stability | Significant (for younger women) | ||||||||
Age | Social and community context | Significant (for younger women) | ||||||||
Race/Ethnicity | Social and community context | Significant (for younger women) | ||||||||
Birthplace | Neighborhood and built environment | Significant (for younger women) | ||||||||
Education | Education access and quality | Significant (for younger women) | ||||||||
23 | Flores et al. (2018) | Cohort study | n = 9,575 | Women who underwent screening mammography in 2005 at Harvard Medical School’s main campus and all affiliated community imaging sites | 50–64 years old | To evaluate the association between PCP, contact and longitudinal adherence with screening mammography guidelines over a 10-year period across different racial/ethnic groups | Race/Ethnicity | Social and community context | Non-significant | Generalized estimating equations, Logistic regression, Linear regression, and Wald chunk tests |
Age | Social and community context | Non-significant | ||||||||
Primary language | Social and community context | Non-significant | ||||||||
Insurance status | Health care access and quality | Significant | ||||||||
Level of primary care physician interaction | Health care access and quality | Significant | ||||||||
24 | Guo et al. (2019) | Cohort study | n = 3,911 | African American participants of the Study on Women’s Health Across the Nation (SWAN) | 45–63 years old | To analyze economic, social, and psychological factors associated with African American women’s adherence to the recommended breast cancer screening guidelines during their mid-age period | Age | Social and community context | Significant | Multinomial logistic regression |
Quality of life | Social and community context | Significant | ||||||||
Employment | Economic stability | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Family income | Economic stability | Significant | ||||||||
Access to healthcare provider | Health care access and quality | Significant | ||||||||
Transportation access | Neighborhood and built environment | Significant | ||||||||
25 | Henderson et al. (2015) | Cohort study | n = 256,470 | Black and white female patients enrolled in the Carolina Mammography Registry from 2005 to 2010 | ≥ 40 years old | To determine if digital screening mammography performs equally well in black and white women | Race | Social and community context | Non-significant | Computed mammography sensitivity, specificity, and positive predictive value (PPV1), random effects logistic regression model, and Chi-square test |
Education level | Education access and quality | Non-significant | ||||||||
Rural/urban area of residence | Neighborhood and built environment | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
26 | Henderson et al. (2020) | Cross-sectional study | n = 393,430 | Women ages ≥40 years receiving screening mammography across three Breast Cancer Surveillance Consortium registries from 2012 to 2017 | ≥ 40 years old | To evaluate barriers to receiving health care, focusing on caretaker responsibilities, health insurance and cost, and transportation | Age | Social and community context | Significant | Chi-square tests, Multivariate logistic regression, and Wald test |
Race/Ethnicity | Social and community context | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Family/Personal history of breast cancer | Social and community context | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
Health insurance costs | Health care access and quality | Significant | ||||||||
Internet access | Neighborhood and built environment | Significant | ||||||||
Local unemployment rate | Economic stability | Significant | ||||||||
English language proficiency | Social and community context/education access and quality | Significant | ||||||||
27 | Henry et al. (2014) | Cross-sectional study | n = 5,197 | Women who received mammography from 2008 to 2010 according to the Utah Behavioral Risk Factor Surveillance System | 40–74 years old | To investigate possible pre-disposing and enabling factors associated with nonadherence to screening guidelines among Utah women 40 years and older using survey data from the Utah Behavioral Risk Factor Surveillance System (BRFSS) | Health care access | Health care access and quality | Non-significant | Descriptive statistics, Bivariate analysis, Wald chi-square tests, and Multivariable logistic regression models |
Age | Social and community context | Significant | ||||||||
Health insurance | Health care access and quality | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
Having a regular physician | Health care access and quality | Significant | ||||||||
Travel time to nearest facility | Neighborhood and built environment | Non-significant | ||||||||
28 | Hong et al. (2018) | Cross-sectional study | n = 196 | Korean American women residing in the Chicago metropolitan area | 50–74 years old | To identify the relationship between perceived discrimination, trust, and breast cancer screening adherence specifically among Korean American (KA) women | Perceived discrimination | Social and community context | Non-significant | Multiple logistic regressions, Firth logistic regressions |
Trust in health care providers/health care systems | Social and community context | Significant | ||||||||
Cultural beliefs | Social and community context | Non-significant | ||||||||
29 | Hubbard et al. (2016) | Cohort study | n = 49,775 | Medicare-enrolled women who underwent a screening mammogram within a registered Breast Cancer Surveillance Consortium (BCSC) program | 66–75 years old | To investigate the sociodemographic factors influencing adherence to screening mammography among older women | Age | Social and community context | Significant | Multivariable logistic regression, Cox proportional hazards regression, and Kaplan–Meier curves |
Income | Economic stability | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Health Literacy | Education access and quality | Significant | ||||||||
Access to healthcare | Health care access and quality | Significant | ||||||||
Diversity index | Social and community context | Significant | ||||||||
Public transportation expenditures | Neighborhood and built environment | Significant | ||||||||
30 | Jena et al. (2017) | Cohort study | n = 95,661 | Women with individual-subscriber or employer-supplemented MA insurance provided through Kaiser | ≥65 years old | To examine the impact of eliminating cost sharing for screening mammography on mammography rates | Age | Social and community context | Significant | Propensity score method, Multivariate logistic regression |
Race/Ethnicity | Social and community context | Non-significant | ||||||||
Insurance status | Health care access and quality | Significant | ||||||||
Neighborhood socioeconomic status | Social and community context/Economic stability | Non-significant | ||||||||
31 | Jensen et al. (2022) | Cross-sectional study | n = 2,065 | Low-income, uninsured, or under-insured women in West Texas who were served by the Access to Breast Care for West Texas (ABC4WT) program | 40–49 years old | To identify sociodemographic barriers and determinants for breast cancer screenings, as well as screening outcomes, in low-income, uninsured, or under-insured communities in West Texas | Age | Social and community context | Non-significant | Pearson’s Chi-square test, T-tests, and Multivariate logistic regression analysis |
Race/Ethnicity | Social and community context | Non-significant | ||||||||
Monthly income | Economic stability | Non-significant | ||||||||
County of residence | Social and community context | Non-significant | ||||||||
32 | Jin et al. (2019) | Cross-sectional study | n = 303 | Korean American women in the Atlanta metropolitan area | 50–80 years old | To investigate the factors linked to mammography screening among Korean American women in the state of Georgia, United States | Health literacy | Education access and quality | Significant | Pearson Chi-square, T-tests, Multiple logistic regression |
Health beliefs | Social and community context | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
Insurance status | Health care access and quality | Significant | ||||||||
33 | Johnson et al. (2021) | Case–control study | n = 3,271 | Idaho residents with ductal carcinoma in situ or invasive breast cancer | 50–64 years old | To assess the time from breast cancer diagnosis to treatment for women enrolled in Idaho’s Women’s Health Check (WHC) Program compared to other female Idaho residents with breast cancer | Socioeconomic status | Economic stability | Non-significant | Chi-square statistics, Stratified Wilcoxon (Van Elteren) tests, Quantile regression |
Age | Social and community context | Non-significant | ||||||||
Race/Ethnicity | Social and community context | Non-significant | ||||||||
Census trace poverty | Economic Stability | Non-significant | ||||||||
34 | Kadivar et al. (2016) | Cross-sectional study | n = 4,249 | Hispanic and non-Hispanic United States-born white women who participated in the National Assessment of Adult Literacy | ≥40 years old | To investigate the connection between functional health literacy and mammography utilization among Hispanic women, in comparison to non-Hispanic White women in the United States | Health literacy | Education access and quality | Significant | Chi-square test, MML probit regression model |
Income | Economic stability | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
Medical insurance | Health care access and quality | Significant | ||||||||
Race/Ethnicity | Social and community context | Significant | ||||||||
35 | Kempe et el. (2013) | Retrospective cohort study | n = 47,946 | Medically insured women who had not undergone a mammogram in the past 24 months | 52–69 years old | To identify the various factors such as race/ethnicity, socioeconomic characteristics, and health status of women who were not screened for breast cancer in an insured population | Age | Social and community context | Significant | Poisson regression models |
Race/Ethnicity | Social and community context | Significant | ||||||||
Language preference | Social and community context | Significant | ||||||||
Insurance | Health care access and quality | Significant | ||||||||
Primary care encounters | Health care access and quality | Significant | ||||||||
Specialty encounters | Health care access and quality | Significant | ||||||||
36 | Khaliq et al. (2015) | Cross-sectional study | n = 250 | Hospitalized women | 50–75 years old | To explore the sociodemographic and clinical factors associated with non-adherence to breast cancer screening among hospitalized women | Race | Social and community context | Non-significant | Logistic regression, Unpaired t-test, and Chi square tests |
Education | Education access and quality | Significant | ||||||||
Annual household income | Economic stability | Significant | ||||||||
Access to primary care physician | Health care access and quality | Significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
37 | Kim et al. (2019) | Retrospective cross-sectional study | n = 127,298 | Females participating in the American Community Survey and Robert Wood Johnson Foundation 500 | 50–74 years old | To evaluate disparities in city-level screening mammography utilization and to identify factors that may impact urban screening utilization | Zip Code/Geography | Neighborhood and built environment | Significant | Mann–Whitney U test, Tukey–Kramer multiple comparison correction, and Spearman rank correlation |
Health insurance | Healthcare access and quality | Significant | ||||||||
Median income level | Economic stability | Significant | ||||||||
Poverty | Economic stability | Significant | ||||||||
Race | Social and community context | Significant | ||||||||
38 | Kim et al. (2022) | Cross-sectional study | n = 497,600 | Females across the United States who participated in the Behavioral Risk Factor Surveillance System in 2012, 2014, 2016, and 2018 | 50–74 years old | To explore the association between diabetes and mammography screening and whether the association varied between racial, ethnic, and geographical groups | Age | Social and community context | Significant | Logistic regression models |
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Employment | Economic stability | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Zip Code/Geography | Neighborhood and built environment | Significant | ||||||||
Median income level | Economic stability | Significant | ||||||||
Health care coverage | Healthcare access and quality | Significant | ||||||||
39 | Komenaka et al. (2015) | Cross-sectional study | n = 1,664 | All female patients seen in the Maricopa Medical Center Breast Clinic in Phoenix, Arizona | ≥40 years old | To investigate the relationship of health literacy and screening mammography | Age | Social and community context | Significant | Two-sample t test, Fisher’s exact test, and Logistic regression analysis |
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Employment status | Economic stability | Significant | ||||||||
Insurance status | Healthcare access and quality | Significant | ||||||||
English as primary language | Social and community context | Significant | ||||||||
40 | Kosog et al. (2020) | Retrospective cross-sectional study | n = 1,161 | Female patients from a single FQHC in a major metropolitan city (Chicago, IL) | 50–74 years old | To identify an association between sociodemographic factors and breast cancer screening adherence in FQHC patients including the homeless | Age | Social and community context | Non-significant | Multivariate logistic regression |
Ethnicity | Social and community context | Non-significant | ||||||||
Primary insurance policy | Healthcare access and quality | Significant | ||||||||
Homelessness status | Economic stability | Significant | ||||||||
Language | Social and community context | Non-significant | ||||||||
Race | Social and community context | Non-significant | ||||||||
41 | Lapeyrouse et al. (2017) | Cross-sectional study | n = 304 | Female Latina participants in 2009–2010 ecological household study | >40 years old | To investigate whether differences in ever having a mammogram exist between Latina border residents by health insurance status, to determine whether those Latinas who reported ever having a mammogram vary by healthcare system, and to investigate the ranking of cost, trust, and familiarity as primary reasons for solely seeking health care in the United States or Mexico | Acculturation | Social and community context | Significant | Frequency statistics, Two-proportion z-test, Binary logistic regression, T-tests, and Chi squared tests |
Age | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Education | Education access and quality | Non-significant | ||||||||
Income | Economic stability | Non-significant | ||||||||
Health insurance status | Healthcare access and quality | Significant | ||||||||
42 | Lawson et al. (2021) | Retrospective cohort study | n = 7,047 | Females diagnosed with breast cancer in Western Washington state | 40–74 years old | To determine factors associated with receipt of screening mammography by insured women before breast cancer diagnosis, and subsequent outcomes | Age | Social and community context | Significant | Multivariable logistic regression analysis, Univariable logistic regression models, Kaplan Meier estimator, Log rank test, and Cox proportional hazards model |
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Zip Code/Geography | Neighborhood and built environment | Significant | ||||||||
Socioeconomic Disadvantage | Economic stability | Significant | ||||||||
43 | Lee et al. (2016) | Cross-sectional study | n = 799,467 | Females who had mammograms performed across five BCSC regional facilities from 2011 to 2012 | ≥40 years old | To compare on-site availability of advanced breast imaging services between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations | Race | Social and community context | Non-significant | Adjusted log binomial generalized estimating equations |
Ethnicity | Social and community context | Non-significant | ||||||||
Household income | Economic stability | Non-significant | ||||||||
Rural/Urban residence, zip code | Neighborhood and built environment | Non-significant | ||||||||
Education | Education access and quality | Non-significant | ||||||||
Access to mammography facilities | Healthcare access and quality | Non-significant | ||||||||
44 | Lee et al. (2017) | Cross-sectional study | n = 168 | Korean American females in the Midwest | 40–79 years old | To investigate breast cancer screening rates and its associated factors in Korean-American immigrant women | Age | Social and community context | Significant | Hierarchical logistic regression analysis |
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Healthcare accessibility | Healthcare access and quality | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Language | Social and community context | Significant | ||||||||
Health care literacy | Healthcare access and quality | Significant | ||||||||
45 | Lee et al. (2021) | Cross-sectional study | n = 2,313,118 | Females attending Breast Cancer Surveillance Consortium affiliated imaging facilities | 40–89 years old | To determine women’s access to and use of DBT screening based on race/ethnicity, educational attainment, and income | Access to DBT | Healthcare access and quality | Significant | Descriptive statistics, Log-binomial regression models, and three-step generalized estimated equations |
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Educational attainment | Education access and quality | Significant | ||||||||
Income | Economic stability | Significant | ||||||||
46 | Li et al. (2020) | Cross-sectional study | n = 12,639 (NHIS) | Civilian noninstitutionalized women living in United States households | 40–74 years old | To identify factors and related inconsistencies associated with mammography use in the entirety of the United States population, as well as between black and white subgroups | Age | Social and community context | Significant | RF analysis; Logistic regression |
Family education | Education access and quality | Significant (NHIS)/Non-Significant (BRFSS) | ||||||||
Family annual income | Economic stability | Significant | ||||||||
n = 169,116 (BRFSS) | Women with telephone access in the United States | Number of children at home | Social and community context | Significant | ||||||
Race (Black) | Social and community context | Significant | ||||||||
n = 181,755 (total) | Women in the United States without a history of breast cancer | Marital status | Social and community context | Mixed | ||||||
Health insurance status | Health care access and quality | Significant | ||||||||
Region | Neighborhood and built environment | Significant | ||||||||
47 | Luo et al. (2021) | Cohort | n = 33,320 | Female Medicare beneficiaries with an initial diagnosis of breast cancer from 2006 through 2014 in the SEER-Medicare database | 67–74 years old | To evaluate the contributions of each tumor biology (histologic grade and hormone receptor status) and healthcare (screening mammography use and time delay from mammography to diagnostic biopsy) factor to racial disparity at breast cancer stage-at-diagnosis between African American and white patients | Race | Social and community context | Significant | Probabilistic graph modeling (PGM) using naïve Bayesian network (NBN)-based contribution analysis |
48 | Molina et al. (2016) | Cross-sectional study | n = 536 | Federally qualified health center (FQHC)-based group of United States-based Latinas in western Washington State who have not obtained a mammogram in the past 2 years | 42–74 years old | To assess the role of four neighborhood characteristics in knowledge-, psychocultural-, and economic-based barriers to mammography use among Latinas | Block group-level socioeconomic deprivation concentration | Neighborhood and built environment/Education access and quality/Economic stability | Non-significant | Multinomial regression models |
Neighborhood socioeconomic-based segregation | Neighborhood and built environment/Economic stability | Significant | ||||||||
Neighborhood Latino-based concentration | Neighborhood and built environment/Social and community context | Significant | ||||||||
Neighborhood Latino-based segregation | Neighborhood and built environment/Social and community context | Significant | ||||||||
Economic | Economic stability/Health care access and quality | Significant | ||||||||
49 | Monsivais et al. (2022) | Cohort study | n = 34,588 | Female patients of a large health care network in Washington State who had completed a mammogram between January 1 and December 31 in 2017 or 2018 but did not have a mammogram in the following year | ≥50 years old | To assess whether racial and socioeconomic inequities in breast cancer screening widened during the COVID-19 pandemic | Age | Social and community context | Significant | Multivariable logistic regression models |
Insurance status | Health care access and quality | Significant | ||||||||
Race or ethnicity | Social and community context | Significant | ||||||||
Rural or urban residence | Neighborhood and built environment | Significant | ||||||||
50 | Nair et al. (2022) | Cohort study | n = 19,292 | BSPAN program participants who had at least one mammogram between 2012 and 2019 | 40–64 years old | To assess prevalence and correlates of baseline adherence, and longitudinal adherence to screening mammograms using data from the longitudinal BSPAN program | Age | Social and community context | Non-significant | Multivariable logistic regression models; multivariable Cox proportional hazards model; chi-square; independent samples t-test; and sensitivity analysis |
Race or ethnicity | Social and community context | Non-significant | ||||||||
Marital status | Social and community context | Significant | ||||||||
Urbanization | Neighborhood and built environment | Non-significant | ||||||||
Proximity to metro | Neighborhood and built environment | Non-significant | ||||||||
Rural | Neighborhood and built environment | Non-significant | ||||||||
Language preference | Social and community context | Significant | ||||||||
Literacy | Education access and quality | Significant | ||||||||
Years lived in the United States | Social and community context | Significant | ||||||||
51 | Onega et al. (2018) | Cross-sectional study | n = 46,944 | Women visiting one of the 15 primary care practices included in the Dartmouth-Hitchock regional network (in NH) and women’s Hospital primary care network (greater Boston) | 40–89 years old | To examine the effect of PCP, practice, and health system-level characteristics and processes on the breast cancer screening metrics of overall percent screened and percent screening past age 75 | Race or ethnicity | Social and community context | Significant | Generalized linear mixed effects regression models; variance components analysis |
Insurance status | Health care access and quality | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
52 | Oviedo et al. (2022) | Cross-sectional study | n = 157 | Women without a history of breast disease who self-identified as Filipino living in the United States, recruited through the national officers of the Philippine Nurses Association of America | ≥40 years old | To determine factors that influence mammogram adherence in Filipino American women using Andersen’s Behavioral Health Model of Services for Vulnerable Populations as the conceptual framework | Breast cancer literacy | Education access and quality | Non-significant | Andersen’s Behavioral Health Model of Services for Vulnerable Populations; logistics regression models; adjusted odds ratios |
Sociocultural deterrents | Social and community context | Non-significant | ||||||||
Cultural beliefs | Social and community context | Non-significant | ||||||||
Years lived in the United States | Social and community context | Non-significant | ||||||||
53 | Padela et al. (2015) | Cross-sectional study | n = 240 | Self-identified Muslim, English-speaking women recruited from 11 CIOGC-affiliated mosques and Muslim organization sites in Greater Chicago | >40 years old | To assess relationships between several religion-related factors and breast cancer screening in a group of Chicago-based Muslim women | Religiosity | Social and community context | Significant | Bivariate testing (ex. unadjusted odds ratios) and multivariate logistic regression models |
Perceived religious discrimination in healthcare | Social and community context | Significant | ||||||||
Age | Social and community context | Significant | ||||||||
Years of residence in the United States | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Non-significant | ||||||||
54 | Paranjpe et al. (2022) | Retrospective cross-sectional study | n = 7,990 | Civilian, noninstitutionalized Asian and non-Hispanic white women who completed the National Health Interview Survey | ≥40 years old | To determine whether breast cancer screening practices were different between Asian and non-Hispanic white women in a national population-based study | Race | Social and community context | Significant | Taylor series linearization methods; Wald chi-square tests; and Multivariable logistic regression |
Insurance status | Healthcare access and quality | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Family income | Economic stability | Significant | ||||||||
Place of Birth in United States | Neighborhood and built environment | Significant | ||||||||
55 | Patel et al. (2014) | Cross-sectional study | n = 334 | Low-income African American women in Nashville, Chattanooga, and Memphis | ≥ 40 years old | To examine socio-demographic factors that influence decision to use mammography and other breast cancer screenings in low-income African Americans and examine differences in obstacles to screening by geographic region | Age | Social and community context | Non-significant | Chi-square test, Binary logistic regression model |
City of residence | Neighborhood and built environment | Significant | ||||||||
BMI | Healthcare access and quality | Significant | ||||||||
Annual household income | Economic stability | Significant | ||||||||
Health insurance status | Healthcare access and quality | Non-significant | ||||||||
Transportation access | Neighborhood and built environment | Significant | ||||||||
Medical visits in the Past 12 months | Neighborhood and built environment | Non-significant | ||||||||
Education | Education access and quality | Non-significant | ||||||||
Employment status | Economic stability | Non-significant | ||||||||
56 | Ryu et al. (2013) | Cross-sectional study | n = 1,596 | Immigrant women in five Asian-American ethnic groups participating in the 2009 California Health Interview Survey | 40–70 years old | To compare rates of screening mammography among immigrant women in five Asian-American ethnic groups in California, and ascertain the extent to which differences in mammography rates among these groups are attributable to differences in known correlates of cancer screening | Age | Social and community context | Non-significant | Wald chi-square design-adjusted test of independence, Multiple logistic regression, Predicted probabilities |
English proficiency | Social and community context | Non-significant | ||||||||
Educational attainment | Education access and quality | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Income | Economic stability | Non-significant | ||||||||
Current health insurance | Healthcare access and quality | Significant | ||||||||
57 | Sabatino et al. (2016) | Cross-sectional study | n = 1,429 (2010) | Female Medicare beneficiaries without breast cancer history between 2010 and 2013 | 65–74 years old | To examine whether mammography use increased after elimination of Medicare cost sharing for screening mammography and whether changes varied for different groups of women | Age | Social and community context | Significant | Pearson Wald F test, Multivariable logistic regression |
Race | Social and community context | Non-significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Birthplace | Neighborhood and built environment | Non-significant | ||||||||
n = 2,152 (2013) | Income | Economic stability | Non-significant | |||||||
Access to Care | Healthcare access and quality | Significant | ||||||||
Type of health insurance | Healthcare access and quality | Significant | ||||||||
Number of provider visits | Healthcare access and quality | Significant | ||||||||
58 | Schommer et al. (2023) | Retrospective cross-sectional study | n = 781 | Breast cancer female patients from Seton Medical Center Austin tumor registry between March 1, 2019 and March 2, 2021 | 40–70 years old | To explore the relationship between COVID-19 (before and after) and stage distribution, time-to-intervention, and insurance status of patients presenting with breast cancer in the Austin local cancer center | Age | Social and community context | Significant | Descriptive statistics, Chi-square test, Fisher exact test, unpaired T-test, Wilcoxon signed-rank test, Multinomial Logistic regression, Two-tailed Wald test |
Sex | Social and community context | Non-significant | ||||||||
Race | Social and community context | Significant (Pre and Post COVID) | ||||||||
Ethnicity | Social and community context | Significant (Pre and Post COVID) | ||||||||
Insurance status | Healthcare access and quality | Significant | ||||||||
Time from breast cancer diagnosis to first treatment | Healthcare access and quality | Significant | ||||||||
59 | Sealy-Jefferson et al. (2019) | Cross-sectional study | n = 7,120 | Racially/ethnically diverse post-menopausal women from the Women’s Health Initiative Survey (1993–2014) | 50–79 years old | To examine whether rural–urban residence was associated with stage at breast cancer diagnosis among large well-defined racially/ethnically diverse cohort of postmenopausal women | Age | Social and community context | Significant | Univariable logistic regression, Multivariable logistic regression |
Race | Social and community context | Non-significant | ||||||||
Ethnicity | Social and community context | Non-significant | ||||||||
Education | Education access and quality | Non-significant | ||||||||
Rural/Urban Residence, Zip Code | Neighborhood and built environment | Non-significant | ||||||||
Social Strain | Social and community context | Non-significant | ||||||||
Health insurance status | Health care access and quality | Non-significant | ||||||||
Social Support | Social and community context | Non-significant | ||||||||
60 | Selove et al. (2016) | Retrospective cohort Study | n = 4,476 | Non-Hispanic Black and White non-HMO Medicare women, who resided in United States, who had a mammogram, biopsy, and breast cancer diagnosis during 2005–2008 | 65–84 years old | Examine the length of critical intervals between abnormal mammogram and breast cancer treatment within a large cohort of Medicare beneficiaries varying by age, race, and medical comorbidities | Age | Social and community context | Significant | Cox proportional hazard models, Logistic regression models |
Race | Social and community context | Non-significant | ||||||||
Ethnicity | Social and community context | Non-significant | ||||||||
Physical comorbidities | Healthcare access and quality | Significant | ||||||||
61 | Shon et al. (2019) | Cross-sectional study | n = 3,710 | Immigrant Asian women who filled the 2005,2007, 2009, and 2011 California Health Interview Survey | ≥40 years old | To examine significant predictors of never having a mammogram among Chinese, Vietnamese, and Korean immigrant women living in California and age 40 years and older and to explore whether relationships between enabling components and acculturation components and odds of never having a mammogram vary across Chinese, Vietnamese, and Korean immigrant women | Ethnicity | Social and community context | Non-significant | Bivariate analysis (Chi-square or ANOVA), Multivariate logistic regression |
Age | Social and community context | Significant | ||||||||
Education | Education access and quality | Non-significant | ||||||||
Federal poverty level | Economic stability | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
Employment | Economic stability | Non-significant | ||||||||
English proficiency | Social and community context | Non-significant | ||||||||
Years lived in the United States | Neighborhood and built environment | Non-significant | ||||||||
Insurance type | Healthcare access and quality | Non-significant | ||||||||
Number of Physician Visits in the past 12 months | Healthcare access and quality | Significant | ||||||||
Number of Chronic Illnesses | Healthcare Access and Quality | Non-significant | ||||||||
62 | Spada et al. (2021) | Retrospective cross-sectional study | n = 35,735 | Female breast cancer patients registered in the Pennsylvania Cancer Registry | 50–64 and 68–74 | To determine if increased access to health insurance following the Affordable Care Act (ACA) resulted in an increased proportion of early-stage breast cancer diagnosis among women in Pennsylvania, particularly minorities, rural residents, and those of lower socioeconomic status | Health Insurance Access | Healthcare access and quality | Non-significant | T-tests; Multivariable logistic regression models; Difference-in-differences analysis |
Area Deprivation Index | Neighborhood and built environment | Non-significant | ||||||||
Race | Social and community context | Significant (for 68–74) | ||||||||
Ethnicity | Social and community context | Significant (for 68–74) | ||||||||
Area of Residence | Neighborhood and built environment | Non-significant | ||||||||
PCP Density | Healthcare access and quality | Non-significant | ||||||||
63 | Tangka et al. (2017) | Cross-sectional study | n = 3,821,084 | Medicaid-insured women in the United States from 2006 to 2008 | 40–64 years old | To assess racial/ethnic and geographic disparities in the use of breast cancer screening | Race | Social and community context | Significant | Regression models; Generalized Estimating Equations (GEE) |
Ethnicity | Social and community context | Significant | ||||||||
State of residence | Neighborhood and built environment | Significant | ||||||||
64 | Thomas et al. (2018) | Retrospective cohort study | n = 14,651 | Medicaid-insured women (not dual enrolled) in California who received treatment in the specialty mental health care system and have filled least one antipsychotic prescription | 48–67 years old | To examine mammogram disparities for those with severe mental illness and the contribution of psychosocial factors to mammogram use among women with severe mental illness | Healthcare access and utilization | Healthcare access and quality | Significant | Poisson models with robust standard errors |
Health insurance status | Healthcare access and quality | Significant | ||||||||
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
County of residence | Neighborhood and built environment | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
65 | Tran et al. (2019) | Cross-sectional study | n = 482,360 | U.S. female survey participants in the 2012, 2014, or 2016 Breast and Cervical Cancer-Screening module of the Behavioral Risk Factor Surveillance System (BRFSS) survey | ≥ 40 years old | To explore urban–rural disparities in United States breast cancer screening practices at the national, regional, and state levels | Area of residence (urban/suburban/rural) | Neighborhood and built environment | Significant | Binary logistic regression models |
Age | Social and community context | Significant | ||||||||
Race | Social and community context | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Healthcare coverage | Healthcare access and quality | Significant | ||||||||
Healthcare access and utilization | Healthcare access and quality | Significant | ||||||||
66 | Vang et al. (2020) | Cross-sectional study | n = 518 | Medically underserved women in NYC | ≥40 years old | To examine the relationship between language preference and screening mammogram adherence | Ethnicity | Social and community context | Significant | Descriptive statistics (Chi-square tests and Fisher’s exact tests), Bivariate analyses and multiple logistic regressions |
Age | Social and community context | Significant | ||||||||
Race | Social and community context | Significant | ||||||||
Education | Education access and quality | Significant | ||||||||
Lack of sufficient healthcare coverage | Healthcare access and quality | Significant | ||||||||
Language | Social and community context | Significant | ||||||||
67 | Virk-Baker et al. (2013) | Cross-sectional study | n = 406,602 | White and Black women in fee-for-service Medicare plans from 203 United States counties with highest risk of breast cancer deaths | 65–74 years old | To assess the uptake of breast cancer screening in women 65–74 years old from counties with most of the breast cancer deaths in Black older women | Race | Social and community context | Non-significant | Logistic regression |
Comorbid conditions | Healthcare access and quality | Non-significant | ||||||||
Age | Social and community context | Non-significant | ||||||||
Education | Education access and quality | Non-significant | ||||||||
ER utilization | Healthcare access and quality | Non-significant | ||||||||
Economic status | Economic stability | Non-significant | ||||||||
68 | Wang et al. (2018) | Cross-sectional study | n = 8,347 | Patients cared by Accountable Care Organizations (ACO) clinics in rural Nebraska with average risk of breast cancer | 50–74 years old | To understand the adherence to the biennial breast cancer screening guideline by rural women with average risk for breast cancer | Age | Social and community context | Significant | Descriptive statistics, Multiple logistic regression, Spearman correlations, and Generalized estimating equation method |
Gender | Social and community context | Significant | ||||||||
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Insurance status | Healthcare access and quality | Significant | ||||||||
Preferred language | Social and community context | Significant | ||||||||
Travel time to clinic | Healthcare access and quality | Significant | ||||||||
County poverty rate | Economic stability | Significant | ||||||||
County uninsured rate | Healthcare access and quality | Significant | ||||||||
Race/Ethnicity composition of county | Social and community context | Significant | ||||||||
69 | Wiese et al. (2023) | Retrospective study | n = 73,718 | Female population in the United States with limited accessibility to mammography (living more than 20-min drive time to nearest mammography facility) | 45–84 years old | To evaluate the travel-time based geographic accessibility to mammography facilities at the census tract level by urban–rural status in continuous US from 2006 to 2022 | Rural vs. Urban/Suburban Setting | Neighborhood and built environment | Non-significant | Descriptive statistics, Regression analysis |
Accessibility to screening facility | Healthcare access and quality | Non-significant | ||||||||
70 | Wilcox et al. (2016) | Cross-sectional study | n = 697 | Randomly sampled households with at least one female tenant selected through 20 United States census tracts with Haitian population | ≥40 years old | To identify the correlation between race/ethnicity and annual mammogram compliance | Age | Social and community context | Significant | Binary logistic regression; Chi-square tests |
Race | Social and community context | Significant | ||||||||
Ethnicity | Social and community context | Significant | ||||||||
Education level | Education access and quality | Significant | ||||||||
Preferred language | Social and community context | Significant | ||||||||
Poverty status | Economic stability | Significant | ||||||||
Employment status | Economic stability | Significant | ||||||||
Insurance coverage | Healthcare access and quality | Significant | ||||||||
Provider visits | Healthcare access and quality | Significant | ||||||||
71 | Wilkerson et al. (2023) | Retrospective cohort study | n = 738 | Female patients who underwent treatment for BC at a quaternary care academic medical center or affiliate zonal hospital | 40–45 years old | To discover if the majority of Black women are diagnosed with breast cancer on their first mammogram and to determine if the connection between patient demographics and primary findings of breast cancer are of importance for preventative care | Age | Social and community context | Significant | Chi-square test; multivariate logistic regression; Wilcoxon rank-sum test |
Race | Social and community context | Significant | ||||||||
BMI | Healthcare access and quality | Significant | ||||||||
Insurance coverage | Healthcare access and quality | Significant | ||||||||
72 | Wu et al. (2021) | Retrospective cohort study | n = 1,044 | Visually impaired women enrolled in fee-for service Medicare | 65–72 years old | To assess whether receiving breast cancer screenings are similar for women w/wo visual impairment | Age | Social and community context | Significant | Chi-square test; Multivariable conditional logistic regression |
Race | Social and community context | Significant | ||||||||
Environment | Neighborhood and built environment | Significant | ||||||||
Insurance coverage | Healthcare access and quality | Significant | ||||||||
Urbanization | Neighborhood and built environment | Significant |
*Statistical significance was assessed based on the p value (p < 0.05).