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. 2024 Feb 7;12:1354717. doi: 10.3389/fpubh.2024.1354717

Social determinants of health and health inequities in breast cancer screening: a scoping review

Vama Jhumkhawala 1, Diana Lobaina 1, Goodness Okwaraji 1, Yasmine Zerrouki 1, Sara Burgoa 1, Adeife Marciniak 1, Sebastian Densley 1, Meera Rao 1, Daniella Diaz 2, Michelle Knecht 1, Lea Sacca 1,*
PMCID: PMC10875738  PMID: 38375339

Abstract

Introduction

This scoping review aims to highlight key social determinants of health associated with breast cancer screening behavior in United States women aged ≥40  years old, identify public and private databases with SDOH data at city, state, and national levels, and share lessons learned from United States based observational studies in addressing SDOH in underserved women influencing breast cancer screening behaviors.

Methods

The Arksey and O’Malley York methodology was used as guidance for this review: (1) identifying research questions; (2) searching for relevant studies; (3) selecting studies relevant to the research questions; (4) charting the data; and (5) collating, summarizing, and reporting results.

Results

The 72 included studies were published between 2013 and 2023. Among the various SDOH identified, those related to socioeconomic status (n = 96) exhibited the highest frequency. The Health Care Access and Quality category was reported in the highest number of studies (n = 44; 61%), showing its statistical significance in relation to access to mammography. Insurance status was the most reported sub-categorical factor of Health Care Access and Quality.

Discussion

Results may inform future evidence-based interventions aiming to address the underlying factors contributing to low screening rates for breast cancer in the United States.

Keywords: social determinants of health, breast cancer screening, mammography, health inequities, underserved women, United States

Introduction

The social determinants of health (SDOH) are factors outside of the realm of medicine that impact health outcomes and quality of life on a daily basis (1). According to the World Health Organization (WHO), SDOH are defined as “the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life (1).” These determinants of health can be divided into five categories: economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context (2). While factors within each of these categories can individually impact a different facet of a person’s health, these categories often also work collectively to create facilitators and barriers to healthy behaviors and health outcomes (1–3). Such SDOH play a significant role in creating new and worsening existing healthcare disparities and may exhibit a stronger influence on health and well-being than the care received by providers and healthcare organizations (4).

One of the most influential roles of SDOH lies within the realm of equitable access to cancer care (4–7). Specifically, when considering breast cancer, there is significant evidence that supports the influence of SDOH on screening. Despite the presence of innovative screening and treatment strategies, breast cancer remains the second most common type of cancer and is a leading cause of disability and mortality in the United States (8). Breast cancer screening, through mammography and clinical breast examination, is the method of primary prevention that is recommended by the United States Preventive Service Task Force (9). However, research studies showed that health disparities persist, as minority women within the United States are less likely to take advantage of breast cancer screening methods (10–14). Though these studies assessed primarily the role of race and ethnicity on breast cancer screening behaviors, they all found that reported associations were mediated by other SDOH such as quality of health care, education, family income, and health insurance (11–14). Hence, there is a need to explore and understand which determinants act as significant influential factors contributing to low breast cancer screening behaviors. This scoping review aims to highlight key SDOH associated with breast cancer screening behavior in United States women aged ≥40 years old, identify public and private databases with SDOH data at city, state, and national levels, and share lessons learned from United States based observational studies in addressing SDOH in underserved women influencing breast cancer screening behaviors. Findings can guide researchers, physicians, and community workers in improving accessibility, affordability, and quality of breast cancer screening opportunities through culturally competent strategies tailored to satisfy the needs of the at-risk female population group.

Methods

The review team consisted of a multidisciplinary team of health professionals with extensive knowledge on the role of SDOH in minority populations. The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was utilized as a reference checklist for the sections of this study (15). The Arksey and O’Malley (16) York methodology was used as guidance for this review. This framework employs five steps: (1) identifying research questions; (2) searching for relevant studies; (3) selecting studies relevant to the research questions; (4) charting the data; and (5) collating, summarizing, and reporting results (16). These methods ensure transparency, permits replicability of the search strategy, and increases the reliability of study findings.

Step 1: identifying research questions

Three research questions were used for this scoping review: (1) What are the major SDOH hindering breast cancer screening in United States women aged > = 40?; (2) What were the major databases/data sources used to capture SDOH data to assess its influence on breast cancer screening behaviors in United States women?; and (3) What are the lessons learned for future recommendations to address SDOH in underserved women at-risk for the disease?

Step 2: searching for relevant articles

Keywords and MeSH terms were developed in collaboration with a research librarian (MK) who is an expert in scoping review protocols. Search terms included: breast cancer, breast cancer screening, mammography, race/ethnicity, education level, income, housing instability, insurance coverage, language preferences, health equity, health disparities, and medically underserved communities, among others. Four electronic databases (PubMed, Embase, Web of Science, and Cochrane) were selected due to their breadth and focus on psychosocial and behavioral aspects of chronic illnesses. These databases were searched to identify peer-reviewed literature from primary data sources, secondary data sources, and case reports. The review of the literature was completed over a period of 3 months, from January 2023 to March 2023. The screening of these articles was carried out by senior author (LS) and co-authors (VJ, DL, GO, YZ, SB, AM, SD, MR, and DD).

Inclusion criteria

The articles that were included were peer-reviewed observational studies, published in English between 2013 and 2023 that focused on the SDOH, including race/ethnicity, employment, education, food security, insurance status, housing, and access to quality healthcare. These observational studies specifically focused on assessing the significance of the role of SDOH in creating health inequities in breast cancer screenings, particularly for women who are 40 years or older, and are at-risk or have been diagnosed with breast cancer. The ≥40 years old age cut-off was selected based on the American Cancer Society recommended guidelines for screening, which highlight that (1) women between 40 and 44 have the option to start screening with a mammogram every year; (2) women 45–54 should get mammograms every year; and (3) women 55 and older can switch to a mammogram every other year, or they can choose to continue yearly mammograms (17).

Exclusion criteria

Excluded studies encompass narrative, scoping, and systematic reviews, as well as qualitative, descriptive, and experimental studies. Additionally, articles were excluded if they did not focus on SDOH as influential factors of breast cancer screening behavior, were assessing knowledge and attitudes rather than exploring SDOH as influencing factors of breast cancer screening, were discussing interventions addressing low breast cancer screening rates and associated disparities that might be related to SDOH, were focusing on survival and mortality rather than screening, and were looking at guideline adherence rather than breast cancer screening behavior itself. Datasets with data collected prior to 2005 were not included in the review.

Step 3: selecting studies relevant to the research questions

All co-authors (VJ, DL, GO, YZ, SB, AM, SD, MR, and DD) extracted, summarized, and tabulated the data from relevant studies. The senior author (LS) reviewed all tabulated data for accuracy and to resolve any discrepancies. Summary tables included an evidence table (Table 1) describing study characteristics, types of SDOH, and outcomes. Types of SDOH were first listed and then categorized based on Healthy People 2030 into five categories: Economic Stability, Education Access and Quality, Health Care Access and Quality, Neighborhood and Built Environment, and Social and Community Context (18). The Healthy People 2030 is a set of science-based objectives with targets to monitor progress and motivate and focus action (18). The Healthy People 2030 first introduced SDOH objectives in 2010, following the World Health Organization’s (WHO) call to address SDOH to maintain health and quality of life (18). The five categories listed reflect the social conditions and environments that are shaped by a wider set of forces and influence behavioral outcomes (18).

Table 1.

Study characteristics.

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
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*Statistical significance was assessed based on the p value (p < 0.05).

Significance of associations between breast cancer screening as an outcome and identified SDOH were reported (Table 1). Table 2 included a list of databases from where the data was accessed, the availability status of the data (public/private), and the geographical level from where the data was extracted. Basic qualitative content analysis was carried out to identify similar themes in future directions across studies highlighted in Table 3. The three phases of qualitative content analysis for the results of primary qualitative research described by Elo and Kyngas (19) were applied: (i) preparation, (ii) organizing, and (iii) reporting.

Table 2.

Database availability status and characteristics.

Primary Author/Year Database/Data source Publicly available (yes/no) City/State/National level
Agenor et al. (2020) National Health Interview Survey (2013–2017) Yes National
Agrawal et al. (2021) Surveys conducted at Three Texas Churches No State
Alabdullatif et al. (2022) National Health Interview Survey (2011–2018) Yes National
Alatrash et al. (2021) Surveys conducted primarily in Arab American mosques and churches No City
Anderson et al. (2014) National Program of Cancer Registries Yes State
Asgary et al. (2014) EHRs from shelter-based clinics of Lutheran Family Health Centers No City
Ayanian et al. (2013) Medicare beneficiary summary file Yes National
Balazy et al. (2019) EHRs from Stanford Health No City
Beaber et al. (2016) EHRs from Dartmouth-Hitchcock Health System and Brigham and Women’s Hospital No City
Beaber et al. (2019) EHRs from 10 PROPSR research medical facilities No National
Calo et al. (2016) United States Census Bureau and Health of Houston Survey Yes City
Castaneda et al. (2014) Survey from UCSD patients 2007–2008 No City
Cataneo et al. (2019) National Health Interview Survey (2015) Yes National
Chandak et al. (2019) Nebraska Cancer Registry (2008–2012) Yes State
Christensen et al. (2023) Medicare Beneficiary Summary File No State
Clark et al. (2017) 2013 US Census American Community Survey Yes State
Clark et al. (2019) National Health Interview Survey (2005, 2008, 2010, 2013, 2015) Yes National
Davis et al. (2017) Surveys conducted at the radiology department of the University of Arizona College of Medicine No State
Dong et al. (2022) Ohio Cancer Incidence Surveillance System (OCISS) No State
Duggan et al. (2019) Surveys conducted at grocery stores, religious organizations, and community events Yes County
Elkin et al. (2014) FDA’s searchable online database of facilities Yes State
Fedewa et al. (2016) National Health Interview Survey (2013) No National
Flores et al. (2018) Institution’s Research Patient Data Registry, MagView, Burtonsville, Maryland No City
Guo et al. (2019) Study of Women’s Health Across the Nation (SWAN) No National
Henderson et al. (2015) Carolina Mammography Registry (CMR) No State
Henderson et al. (2020) Breast Cancer Surveillance Consortium (BCSC), a National Cancer Institute (NCI)-funded network of mammography registries across the United States. No National
Henry et al. (2014) The 2008 and 2010 Utah Behavioral Risk Factor Surveillance System No State
Hong et al. (2017) Questionnaires No City Level
Hubbard et al. (2016) Breast Cancer Surveillance Consortium (BCSC) Yes National Level
Jena et al. (2017) Kaiser Permanente MA plans No State level
Jensen et al. (2022) Access to Breast Care for West Texas (ABC4WT) No State level
Jin et al. (2019) Self-report survey questionnaires No State level
Johnson et al. (2021) Cancer Data Registry of Idaho (CDRI) Yes State level
Kadivar et al. (2016) National Assessment of Adult Literacy (NAAL) Yes National Level
Kempe et el. (2013) Kaiser Permanente Colorado (KPCO) No State level
Khaliq et al. (2015) Bedside interviews No City
Kim et al. (2019) American Community Survey and Robert Wood Johnson Foundation 500 Cities Project with data from Behavioral Risk Factor Surveillance System Yes City
Kim et al. (2022) Cross sectional data from 2012, 2014, 2016, and 2018 Behavioral Risk Factor Surveillance System Yes National
Komenaka et al. (2015) Maricopa Medical Center Breast Clinic data No City
Kosog et al. (2019) FQHC Electronic Medical Record No City
Lapeyrouse et al. (2017) 2009–2010 Ecological Household Study on Latino Border Residents in El Paso County, TX No City
Lawson et al. (2021) Insurance enrollment data from regional commercial insurers and Medicare liked with records from the Cancer Surveillance System from 2007–2018 No State and National
Lee et al. (2016) Breast Cancer Surveillance Consortium Yes National
Lee et al., 2017 Baseline data from mobile phone program “mMammogram” No State/Regional
Lee et al. (2021) Breast Cancer Surveillance Consortium Yes National
Li et al. (2020) 2016 National Health Interview Survey Yes National
2016 Behavioral Risk Factor Surveillance System Yes National
Luo et al. (2021) SEER Medicare Yes National
Molina et al. (2016) 2011–2014 Fortaleza Latina! Yes State
Monsivais et al. (2022) Patient data from MultiCare health system, a large state-wide, non-profit healthcare system with 230 clinics and hospitals across Washington State No State
Nair et al. (2022) 2012–2019 electronic health record data for BSPAN program participants Yes State
Onega et al. (2018) PROSPR research centers including the primary care populations of the Dartmouth-Hitchock regional network (in NH) and the Brigham and Women’s Hospital primary care network (in greater Boston) Yes National
Oviedo et al. (2022) Self-administered, web-based surveys sent through the PI’s network of friends and through the national officers of the Philippine Nurses Association of America and further through snowball recruitment No National
Padela et al. (2015) Self-administered surveys given to participants at sites affiliated with the Council of Islamic Organizations of Greater Chicago (CIOGC) in the Chicago metro area No City
Paranjpe et al. (2022) 2015 National Health Interview Survey Yes National
Patel et al. (2014) Meharry CNP Community Survey Database No State
Ryu et al. (2013)* 2009 California Health Interview Survey Yes State
Sabatino et al. (2016) National Health Interview Survey Data Yes National
Schommer et al. (2023) Seton Medical Center Austin Tumor Registry No City
Sealy-Jefferson et al. (2019) Women’s Health Initiative Program (WHI) No National
Selove et al. (2016) Center for Medicare and Medicaid Services (CMS) No National
Shon et al. (2019) California Health Interview Survey data Yes State
Spada et al. (2021) Pennsylvania Cancer Registry Yes State
Tangka et al. (2017) Fee-for-service claims and encounter data from Centers for Medicare and Medicaid Services No National
Thomas et al. (2018) California Medicaid (Medi-Cal) Administrative, Pharmacy, and Billing Systems No State
Client and Service Information System
Tran et al. (2019) Behavioral Risk Factor Surveillance System surveys (BRFSS) Yes National
Vang et al. (2020) Participants of breast health education programs at various communities and faith-based organizations in MU areas of NYC No City
Virk-Baker et al. (2013) Medicare claims data for outpatient procedures, physician visits and inpatient stays from 2001–2006 Yes National
Wang et al. (2018) Clinic EMRs and provider surveys from an ACO organization No State
Secondary data obtained from Area Health Resource File administered by Health Resources and Services Administration
Wiese et al. (2023) US FDA, BRFSS Yes National
Wilcox et al. (2016) US Department of Health Yes State
Wilkerson et al. (2023) U.S Department of Health Yes National
CDC
Prevention and National Cancer Institute
JNCI
Wu et al. (2021) Medicare database No National
Clinical Modification (ICD-9-CM) billing codes
Current Procedural Terminology (CPT)
Healthcare Common Procedure Coding System (HCPCS)
Young et al. (2020) FDA’s mammography facility database Yes State
American Community Survey US Census Rural -Urban community (RUCA) codes
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*For one control variable, county-level PCP data were obtained across the state from a different database: Area Health Resources Files.

Table 3.

Lessons learned identified from thematic analysis across included studies.

Lessons learned themes

  1. Lack of health insurance was strongly associated with lower breast cancer screening rates across various populations.

  2. Functional health literacy was found to be significantly associated with mammography receipt; however, the relationship between health literacy and mammography can be influenced by factors such as ethnicity and language-preference acculturation.

  3. Economic factors such as poverty level was a strong indicator of breast cancer screening rates.

  4. Geographic factors including regional poverty are associated with increased late-stage breast cancer and lower breast cancer screening rates.

  5. Rural areas were associated with less access to on-site breast cancer screening access and had lower overall breast cancer screening rates.

  6. Women who identified themselves as nonwhite ethnicity, with the exception of Asians, had a higher likelihood of being unscreened.

  7. Asian women with less time spent in the U.S. and Korean populations had lower screening rates due to limited acculturation, lack of education surrounding breast cancer screening, and lack of insurance.

  8. There is a need to address culturally specific barriers, such as distrust of physicians, which may increase Black women’s confidence in breast cancer screenings and motivation to have preventive breast cancer care.

  9. Methods to enhance patient–provider communication may be important to increasing adherence to mammogram screening guidelines for those reporting less than ideal interactions with healthcare providers.

  10. The COVID-19 pandemic was correlated with lower screening rates in women, possibly due to limited healthcare access for individuals.

  11. Breast cancer screening and adherence rates differed depending on the religious values of certain populations, more specifically, fatalism-emphasizing religions led to less screening adherence.

  12. Cultural efforts include developing culturally appropriate interventions and training health professionals in culturally competent communication skills, while structural efforts include removing barriers to access, improving health insurance coverage, language proficiency, and transportation services.

  13. Community-tailored educational campaigns to reinforce the importance of establishing yearly mammogram screening behaviors can be powerful and effective tools for increasing adherence across various populations.

  14. Facilitating access to IT may help increase mammography utilization, which may contribute to eliminating disparities in breast cancer mortality.

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Step 4 and 5: charting the data and collation, summarization, and reporting of results

Study characteristics were tabulated for 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), and type of methodology/analysis used for data analysis (Table 1). Identified databases were tabulated by primary author/year, database/data source, public availability, and city/state/national level (Table 2). Each database was stratified based on availability (publicly available/not publicly available) and location (city/state/national level). Lessons learned from each relevant study were highlighted in Table 3.

Results

The initial study extraction resulted in 8,124 articles from PubMed (n = 1,293), EMBASE (n = 6,193), Web of Science (n = 527), and Cochrane (n = 111). Studies were excluded due to publication outside of the timeframe (n = 7,775), discussion of all types of cancer rather than focusing on breast cancer (n = 2,349), being a literature review or systematic review (n = 884), lack of focus on breast cancer disparities (n = 717), focusing on big data or no mention of SDOH (n = 124), focusing more on knowledge and attitudes rather than SDOH (n = 112), being an opinion piece or an editorial (n = 25), or emphasizing survival as an outcome rather than treatment (n = 22). Duplicate studies were also excluded (n = 82 from PubMed, n = 60 from EMBASE, n = 20 from Web of Science, and n = 2 from Cochrane). A total of 267 studies met the inclusion criteria from PubMed (n = 222), EMBASE (n = 40), and Web of Science (n = 5). An additional 195 studies were excluded after a full study review due to being an abstract and not a full text (n = 77), having a qualitative or experimental study design (n = 42), having no relation to SDOH (n = 63), and discussing cancer types in general rather than narrowing it down to breast cancer (n = 13). A total of 72 studies were retained for analysis (Figure 1).

Figure 1.

Figure 1

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PRISMA-ScR flow chart of study selection process.

The 72 included studies were published between 2013 and 2023. About half of the studies (58%) were published in 2018 or later (n = 42). Study designs included cross-sectional studies (n = 45); cohort studies (n = 18); and case–control studies (n = 9). Sample size ranged from n = 100 to n = 3,821,084 female adults with breast cancer while the age of this target population ranged from 40 to 89 years old (Table 1).

Priority populations

Priority populations who were actively involved (or targeted) in implementation activities were ethnically diverse female patients diagnosed with breast cancer including African American women; Muslim and Christian Arab American; Haitian women; Filipino women; and Korean American women. Another set of studies focused on women from programs, such as women from Geisel School of Medicine (n = 3,413), from the BSPAN program (n = 19,292), women who underwent mammography in Harvard Medical School (n = 9,575), female patients from a single institution undergoing breast radiotherapy (n = 1,057), presenting to radiology department (n = 758), mammogram facilities (n = 1,749), and at a quaternary care academic medical center (n = 738) (Table 1).

Additional studies focused on the characteristics of the women, such as women who have individual subscribers or employer supplemented (n = 95,661), are Medicaid-insured and Medicare fee-for service (n = 11), are insured but have not undergone mammogram in 24 months (n = 47,946), have no history of breast cancer (n = 181,755), have telephone access (n = 169,116), homeless women (n = 100), hospitalized women (n = 250), are medically underserved (n = 518), and have limited accessibility to mammogram (n = 73,718) (Table 1).

Classification of SDOH factors influencing breast cancer screening behavior based on the healthy people 2030 categories

An examination of SDOH influential factors of breast cancer screening was conducted, focusing on their classification into Healthy People 2030 categories (20). Among the various SDOH identified, those related to socioeconomic status (n = 96) exhibited the highest frequency (Table 1). Specifically, factors such as income (n = 32), education level (n = 29), employment status (n = 8), birthplace/citizenship (n = 5), acculturation/years lived in the United States (n = 5), marital status (n = 2), social support (n = 2), and number of children (n = 1) were among the key elements. Access to healthcare (n = 75) emerged as a significant theme, with subcategories like insurance status (n = 33), accessibility of healthcare services and providers (n = 18), insurance coverage (n = 8), access to mammography facilities (n = 5), insurance copayments (n = 2), time from breast cancer diagnosis to first treatment (n = 1), travel time to clinic (n = 1), and county uninsured rate (n = 1) also being identified. Race/Ethnicity (n = 79), age (n = 52), sex/gender (n = 2), and sexual orientation (n = 1) were additional factors reported. Language-related SDOH (n = 21) were observed 21 times, encompassing language proficiency/preferred language (n = 15) and health literacy (n = 6). Furthermore, location (n = 30), transportation (n = 5), housing (n = 3), county poverty rate (n = 2), internet access (n = 1), area deprivation index (n = 1), diversity index (n = 1), cultural and religious beliefs (n = 4), perceived discrimination (n = 2), health beliefs (n = 1), and trust in health care providers/systems (n = 1) were also cited. Finally, health-related factors (n = 9) that were reported include comorbidities and chronic illnesses (n = 3), BMI (n = 2), medical/family history of breast cancer (n = 1), history of mental illness (n = 1), HIV status (n = 1), and substance/alcohol abuse (n = 1) (Table 1). Among the Healthy People 2030 categories, Social and Community Context (n = 177) emerged as the most prevalent, with a striking 177 occurrences of SDOH. Following closely behind were Healthcare Access and Quality (n = 80), Economic Stability (n = 56), Neighborhood and Built Environment (n = 46), and Education Access and Quality (n = 36) (Table 1).

Database access and characteristics

Databases with the highest number of occurrences include data from the National Health Interview Survey (n = 8) [over a range of years from 2005 to 2018], the Breast Cancer Surveillance Consortium (n = 4), and the United States Department of Health (n = 2). Other databases used include the National Program of Cancer Registries, the National Assessment of Adult Literacy, and SEER Medicare. Of the 74 databases used, 47% (n = 35) are publicly available. The databases are available at the city (n = 16), county (n = 1), state (n = 28), and national (n = 30) levels (Table 2).

Significance of association between SDOH factors and access to mammography and treatment opportunities

The Health Care Access and Quality category was reported in the highest number of studies (n = 44; 61%), showing its statistical significance in relation to access to mammography. Insurance status was the most reported sub-categorical factor of Health Care Access and Quality with n = 36 (50%) articles supporting this finding. A total of n = 42 (58%) studies showed statistical significance in the social and community context category, with the highest subcategories being age and ethnicity with n = 46 (63%) and n = 40 (55%) articles denoting their significance, respectively. Language was the third highest with n = 11 (15%) studies highlighting its significance as an influential factor of screening behavior. Further, n = 28 (38%) studies exhibited statistical significance under the Economic Stability category, with income level being the most common sub-categorical indicator emphasized in n = 20 (27%) studies. Next, the Neighborhood and Built Environment category showed statistical significance in n = 18 (25%) articles, with zip code or geographic location being reported as the strongest sub-categorical indicator in n = 15 studies (20%). Moreover, n = 24 (33%) articles showed statistical significance in Education Access and Quality as strong indicators of mammography rate, with the highest level of education completed acting as the strongest sub-categorical factor in n = 24 (33%) articles (Table 1).

The methodology used across the included studies to communicate statistical data were reported as: logistic regression (n = 63), descriptive statistics (n = 23), chi-square tests (n = 20), T-tests (n = 13), linear regression (n = 9), multivariate analyses (n = 9), Wald tests (n = 8), Generalized estimating equations (n = 7), Spatial analysis (n = 7), Cox proportional hazards regression (n = 5), Kaplan–Meier cumulative incidence (n = 3), Sensitivity analysis (n = 2), Trend analysis (n = 2), and Z tests (n = 1) (Table 1).

Lessons learned

Using the three phases of qualitative content analysis delineated by Elo and Kyngas (19), qualitative themes were identified. First, data relevant to lessons learned was collected from each of the included studies in the preparation stage (Phase I) (Supplementary material 1). Second, lessons learned were organized into bullet points and tabulated by primary author to compare data across studies and explore emerging themes (Phase 2) (Supplementary material 1). Major themes were then highlighted in Table 3 (Phase III).

Many of the studies demonstrated a strong association between a lack of health insurance and a lower rate of breast cancer screening (21–25). Ethnic minority women, with the exception of those identifying as Asian, had a lower likelihood of being screened, and Black women experienced a higher risk of diagnosis upon first screening (25–29). While few studies analyze the effect of sexual orientation on breast cancer screening, initial insights reveal there are significant differences in mammography between bisexual, lesbian, and heterosexual women regardless of racial/ethnic groups (30). In considering religious values, fatalism-emphasizing religions were associated with less screening adherences and maintenance of modesty did not prove a significant limitation for women receiving mammograms (31–33). Economic factors present limitations as both high levels of poverty and impoverished rural regions were associated with lower screening rates (27, 32, 34–37). Improving patient-provider communication, addressing perceived discrimination, and improving trust in the health care system is necessary to improve screening rates across all demographics (38–42). Additionally, structural efforts to improve health insurance coverage, language proficiency, and transportation services could be beneficial (20–110). These steps will need to involve the local community to develop community-tailored educational campaigns to reinforce the importance of establishing yearly mammogram screenings (Table 3) (22, 34, 46, 49, 54, 55, 70, 76, 80, 86).

Discussion

The purpose of this scoping review was to identify the major SDOH acting as influential factors of breast cancer screening in United States women aged ≥ 40 years old. The analysis of the 72 included studies can inform which SDOH categories to focus on when designing evidence-based interventions for more effective and sustained positive behavior and health outcomes among United States women at-risk of breast cancer.

SDOH factors and healthy people 2030 categories

Of the classifications of SDOH by Healthy People 2030, the Social and Community Context Category was the most prevalent across the included studies (n = 177). However, when looking at the most frequently cited SDOH influential factors of breast cancer screening behaviors, those related to socioeconomic status exhibited the highest frequency. Such factors included income (n = 32), education level (n = 29), employment status (n = 8), birthplace/citizenship (n = 5), acculturation/years lived in the United States (n = 5), marital status (n = 2), social support (n = 2), and number of children (n = 1). Other highly reported factors include insurance status (n = 33) under the Healthcare Access and Quality category, as well as race/ethnicity (n = 79) and age (n = 52) under the Social and Community Context Category.

There is evidence to show the significance of the relationship between socioeconomic factors and breast cancer screening. Over 30 different interventions that address SDOH increased breast cancer screening rates by 12.3% (93). Social determinants such as poverty, lack of education, neighborhood disadvantage, residential segregation, racial discrimination, lack of social support, and social isolation have shown in numerous studies to play a role in the breast cancer stage at diagnosis (94, 95). Gomez et al. (94) highlighted in their review that social and built environments have been shown to factor into cancer diagnoses in 82% of 34 reviewed articles published since 2010, including breast cancer (96). Studies have found that, not only do these factors have a significant association with breast cancer screening individually, but they also work dynamically to impact screening and treatment for breast cancer (97).

Low affordability and healthcare accessibility profoundly impact breast cancer screening, leading to lower adherence in female patients. For instance, Medicaid patients who are required to pay co-payments for preventative services as well as for recommended follow-up visits are less likely to pursue such preventative services and mammograms are included in lost care (96). Co-payments of more than $10 have been associated with reduced rates of mammograms (97). Furthermore, a study investigating breast cancer screening among young military women revealed that, when removing cost and access barriers to obtaining a breast mammography, first-time screening rates were 90% (98). Similar results have been noted when patients were provided free mammograms in underserved areas. The Building Relationships and Initiatives Dedicated to Gaining Equality (BRIDGE) Healthcare Clinic, a free clinic offered by the University of South Florida, provided patients free mammograms and noted that about 84.5% of patients utilized these services (99).

Significance of associations between SDOH factors and breast cancer screening and treatment

The majority of the studies reported a significant association between the SDOH factors under each of the five Healthy People 2030 categories. Insurance status was the most reported sub-categorical factor of Health Care Access and Quality with n = 36 (50%) articles supporting this finding. Insurance status often determines whether patients seek mammography services as they often become costly without robust coverage (93). Despite stable mammography rates among women in the United States between the years 2000 and 2015, women who report being uninsured consistently have the lowest rates of mammography at 35.3% (100).

Moreover, a total of n = 42 (58%) studies showed statistical significance in the social and community context category, with the highest subcategories being age and ethnicity with n = 46 (63%) and n = 40 (55%) articles denoting their significance, respectively. Health disparities in the United States have been consistently associated with delayed screening, which then contributes to higher mortality rates among both Hispanic and Black populations (28). Inequities also exist in mammography rates between patients of different sexual orientations (111). White, bisexual women had significantly lower mammography rates than White, heterosexual women, while mammography rates were significantly higher for bisexual, Black women than for heterosexual, Black women (102).

Income (n = 20; 27%) strongly influences mammography rates since women with estimated household incomes greater than $38,100 have been found to have rates of repeat mammography higher than those of women below $25,399 (109). In addition to household income, food security acts as another influential factor of mammography rates. When patients are forced to choose between feeding their families and pursuing preventative care, mammography becomes more of a luxury than lifesaving care (110). Women facing food insecurity have shown a 54% lower likelihood of obtaining mammography (110).

Language (n = 11; 15%) and availability of translation services, health literacy, and culture also play a strong role in mammography rates since many women with limited English proficiency seek mammography care and receive abnormal results (103). Appropriate, timely follow-up in the correct language is imperative to proper care provision; however, a lack of translation services worsens the language barrier between these patients and their healthcare providers, delaying care (101). Clinics with a patient population that is majority non-English speaking also experience greater follow-up delays than those with a minority of non-English speakers due to language barriers (103). The lower a patient’s health literacy, the less likely they are to undergo up-to-date breast cancer screening according to official guidelines (104, 105). The cultural and religious beliefs in fatalism have also been continuously found to be associated with lower mammography rates, whereby women with the highest beliefs in fatalism had the lowest breast cancer screening rates (106, 107).

Finally, Education Access and Quality sub-categories were significant indicators of mammography rate, with the highest level of education completed acting as the strongest sub-categorical factor in n = 24 (33%) articles. A systematic review by Damiani et al. (109) showed that United States women with the highest level of education were more likely to screen for breast cancer, with a 36% higher rate of adherence to national screening guidelines compared to women with lower levels of education. This finding holds health professionals and community outreach efforts accountable in ensuring that the local patient population is aware of the importance of and has access to breast cancer screening measures (109, 110).

Availability of public databases

Of the 74 databases used, only 47% (n = 35) were publicly available. There is a need to establish more widely accessible databases encompassing a routine collection of data on the SDOH to allow for the examination of additional evidence on exiting associations between SDOH and health outcomes. These databases could also inform the development and implementation of longitudinal and experimental studies at the county, city, and national levels to decrease health disparities exacerbated by SDOH factors.

Strengths and limitations

Despite the importance of this study in guiding and informing the development and implementation of future SDOH-oriented evidence-based interventions for breast cancer screening, findings need to take into consideration this study’s limitations. First, despite a comprehensive search of the literature in psychosocial databases compatible with the topic at hand, this review did not include gray literature and did not encompass tracing of reference lists in included studies. Second, it also was limited to observational studies to explore SDOH factors acting as factors based on statistical tests looking at significance of reported associations. These observational studies also widely varied in reported sample sizes, ranging from 100 participants to a population of 4 million. Therefore, although statistical significance was reported across different studies, effect sizes, power, and external validity varied greatly. Future systematic reviews should assess the rigor and quality of analysis carried out, evaluate recruitment efforts and data collection methods, and critique analytical tests carried out to account for the difference in sample sizes. Third, the mesh terms included as many technical words and keywords relevant to the SDOH as possible but might have inadvertently omitted some key words due to the continuously evolving and changing definitions related to SDOH. However, the help of an expert research librarian mitigated the impact of this concern by imposing rigor in implemented scoping review protocols when developing the search strategy for this review. Fourth, formal assessment of the methodology and quality of the evidence was beyond the scope of this study and relied on the reported statistical tests to assess significance. Follow-up systematic reviews would help with addressing this limitation by focusing specifically on the analytical proportion of each study. Fifth, although various categorizations exist for SDOH such as the WHO and CDC categories, the Healthy People 2030 taxonomy was adopted for use as it is the most recently updated classification encompassing a wide range of SDOH. Future studies should compare these taxonomies by feasibility, usability, and importance for a more valid and systematic approach to SDOH categorization.

Conclusion

This scoping review describes major SDOH acting as significant influential factors of breast cancer screening behaviors among United States women aged ≥40 years old who are at-risk of the disease. Results may inform future evidence-based interventions aiming to address the underlying factors contributing to low screening rates for breast cancer in the United States. Efforts to integrate SDOH within the different components of intervention planning, implementation, and sustainability are widely gaining recognition, particularly in underserved communities, due to their substantial influence on everyday behaviors.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

VJ: Conceptualization, Data curation, Methodology, Writing – original draft. DL: Conceptualization, Data curation, Methodology, Writing – original draft. GO: Conceptualization, Data curation, Methodology, Writing – original draft. YZ: Conceptualization, Data curation, Methodology, Writing – original draft. SB: Conceptualization, Data curation, Methodology, Writing – original draft. AM: Conceptualization, Data curation, Methodology, Writing – original draft. SD: Conceptualization, Data curation, Methodology, Writing – original draft. MR: Conceptualization, Data curation, Methodology, Writing – original draft. DD: Methodology, Writing – original draft. MK: Methodology, Software, Writing – review & editing. LS: Conceptualization, Investigation, Methodology, Project administration, Supervision, Validation, Writing – review & editing.

Funding Statement

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2024.1354717/full#supplementary-material

Click here for additional data file. (40.9KB, XLSX)

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Data Availability Statement

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