Abstract
Background: Cancer is a major public health concern in the United States, especially among minority populations. Area-level social determinants of health (SDOH) influence cancer outcomes, but the impact of the Minority Health Social Vulnerability Index (MHSVI) on cancer incidence at the county level is less understood.
Methods: We analyzed ecological data from the Agency for Health Care Research and Quality for 3,232 counties in 2019. Exposures included MHSVI themes: socioeconomic, household composition, minority status/language, housing/transportation, healthcare infrastructure/access, and medical vulnerability (continuous). Overall MHSVI was categorized into low (.01/.25), moderate (.26/.74), and high (.75/1) percentiles. The outcome was the total number of cancer cases (continuous). Covariates included US regions and rural-urban regions. Unadjusted and adjusted negative binomial regressions with population weighting were performed using STATA/MPv.17; P values ≤0.05 were considered statistically significant.
Results: A total of 3,232 counties were analyzed, with an average of 2,817.9 (SD:7,733.5) cancer cases, ranging from 16 to 201,547. All variables were significantly associated with cancer cases in unadjusted analyses. Adjusted analysis showed increased cancer incidence in moderate (IRR:0.94, 95%CI:0.92-0.96, P<0.001) and high (IRR:0.86, 95%CI:0.84-0.88, P<0.001) MHSVI areas compared to low MHSVI areas. Regional differences were observed, with increased cancer incidence in the Northeast (IRR:1.18, 95%CI:1.15-1.22, P<0.001), South (IRR:1.03, 95% CI:1.01-1.05, P<0.001), and West (IRR:0.92, 95%CI:0.90-0.94, P<0.001) compared to the Midwest. Rural areas had a slight increase in cancer incidence compared to urban areas (IRR:1.03, 95%CI:1.01-1.04, P<0.001).
Conclusions: Our study highlights the significant association between MHSVI and cancer incidence at the county level. Regional and rural-urban differences were evident, emphasizing the need for targeted interventions addressing SDOH to reduce cancer disparities.
- Cancer incidence
- Minority Health Social Vulnerability Index
- Regional
- Rural-urban
- Social determinants of health
Although there has been significant progress in cancer-related care and outcomes, cancer remains a significant public health concern in the United States, with an estimated 1.9 million new cancer incidents diagnosed and approximately 600,000 cancer-related deaths in 2021 alone.1 Unfortunately, there are significant disparities in health that result in certain populations, namely racial and ethnic minorities, being disproportionately affected by the burdens of cancer.2 This disparity highlights an urgent need to understand and address the factors contributing to these inequities, particularly the social determinants of health (SDOH).
Neighborhood-level SDOH, such as socioeconomic status, access to healthcare, and living conditions, are known to play a crucial role in shaping health disparities in cancer incidence and outcomes.3,4 These factors can influence cancer screening, prevention, and treatment, thus contributing to disparities in cancer incidence and survival rates among different population groups.5 SDOH such as the Minority Health Social Vulnerability Index (MHSVI) is a novel tool that allows for an objective measurement of the multiple aspects of social vulnerability as it relates to minority healthcare, and includes socioeconomic status, household composition, minority status/language, housing/transportation, healthcare infrastructure/access, and medical vulnerability.6 While some studies have explored the specific components of social vulnerability and their association with cancer incidence,7 little is known about the combined effects of these factors as captured by the MHSVI.
The outcome the MHSVI has on cancer incidence at the county level, in addition to potential differences that may exist between urban and rural neighborhoods, is not yet fully understood. Our study aimed to address these knowledge gaps by investigating the impact of MHSVI on population-based cancer incidence at the county level utilizing data from the Agency for Health Care Research and Quality (AHRQ) from 2019 for 3,232 counties. The impact of minority health social vulnerability on population-based cancer incidence is a relevant area of research at this time in the United States, as it is steadily becoming more and more diverse. A greater understanding of the factors contributing to cancer disparities is essential to ensure equitable access to prevention, screening, and treatment services.8 The methodology employed in this study is designed to provide an initial exploration into the association between social vulnerability and cancer incidence at the county level. While our results contribute valuable insights, they should be viewed as a foundational step toward more comprehensive future studies that can better inform stakeholders in making evidence-based decisions. This research not only contributes to a growing body of evidence on the role of social determinants in shaping cancer disparities but also has the potential to guide policy and practice in addressing these disparities in the US.
Methods
Data Sources and Population
In our ecological study, we conducted a cross-sectional design to examine the impact of the MHSVI on population-based cancer incidence across 3,232 counties in the United States and its territories. We sourced county-level data from the 2019 AHRQ SDOH database, which provides nationwide, comprehensive data on the various SDOH variables across domains of social, economic, healthcare, and environmental factors that ultimately impact health outcomes.9 This database serves as an invaluable resource for researchers, policymakers, and public health professionals to better understand and address health disparities and social inequities at both community and population levels.
For our research question, the 2019 version of the AHRQ SDOH database was most suitable, as data for zip codes and census tracts were not available. This version includes updated SDOH indicators, allowing for the analysis of current trends in SDOH across the country. The SDOH database has been thoroughly described in our previous study.10 Our study population encompassed all 3,232 counties in the United States and its territories, providing a nationally representative sample for a robust examination of the relationship between MHSVI and cancer incidence. By utilizing county-level data from the AHRQ SDOH database, we were able to gain comprehensive insights into various social determinants at the county level and their potential impact on cancer incidence nationwide.
Study Measures
The dependent variable (study outcome) was the total number of cancer cases (continuous) at the county level.11 These data were derived from the U.S. Cancer Statistics (USCS), produced annually by the U.S. Department of Health and Human Services (HHS), Centers for Disease Control and Prevention (CDC), Division of Cancer Prevention and Control.12 The USCS estimates the cancer burden across states based on publicly reported public health surveillance systems and provides cancer statistics for multiple geographic areas, including state, county, and health service areas.12 County-level data were available in the AHRQ SDOH database, which spans the SDOH domain of the healthcare context.13 The SDOH database county data files contain a 5-year average of cancer incidence from the USCS.12 These data were drawn directly from the USCS website and renamed and merged for clarity and consistency with other variables.13 Data were available at the county level, but county-level case data were not available from Kansas and Minnesota due to state legislation and regulations.12 Suppression rules are implemented in the source data, including suppressing rates and counts if fewer than 16 cases were reported in a specific category or if a state requested suppressions for race and ethnicity.12
The independent variable was MHSVI, which was developed by the Office of Minority Health at the US HHS14 and is related to the Social Vulnerability Index (SVI) developed by the CDC.15 MHSVI comprised six continuous themes: socioeconomic, household composition, minority status/ language, housing/transportation, healthcare infrastructure/ access, and medical vulnerability.14 Each theme addresses a different aspect of social vulnerability, focusing on minority populations. Socioeconomic status includes indicators such as income, poverty, unemployment, and education levels, which can impact health outcomes and access to resources. Household composition considers factors such as household size, family structure, and the presence of children or elderly individuals, potentially affecting households’ ability to cope with adversity and access healthcare services. Minority status/language encompasses the proportion of minority populations and individuals with limited English proficiency, influencing access to healthcare services, social support, and care providers’ cultural competence. Housing/transportation addresses indicators related to housing quality, affordability, and transportation access, which can affect health and the ability to access healthcare services. Healthcare infrastructure/ access consists of factors such as the availability of healthcare facilities, providers, and insurance coverage, impacting access to care and health outcomes. Medical vulnerability considers the prevalence of chronic conditions, disability, and other health risk factors within the population, which can exacerbate vulnerability to adverse health outcomes. The MHSVI, as a composite measure, captures various dimensions of social vulnerability with a particular focus on minority populations. The MHSVI is interpreted by examining its component themes and their respective scores, ranging from 0 to 1, which reflect the level of social vulnerability within a specific geographic area, such as a county. Higher scores indicate greater vulnerability, while lower scores suggest reduced vulnerability. We divided the overall MHSVI into low (0.01-0.25), moderate (0.26-0.74), and high (0.75-1) percentiles, further assisting in the identification of areas with varying vulnerability levels.
Covariates included US regions (Midwest, Northeast, South, West), and rural-urban regions.16 The CDC NCHS Urban-Rural Classification Scheme for Counties is a system developed by the CDC’s National Center for Health Statistics (NCHS) to classify counties in the US based on their degree of urbanization. This classification scheme helps researchers, policymakers, and public health practitioners to better understand and address health disparities and differences in health outcomes across urban and rural areas. The original classification scheme consists of six categories, ranging from large central metropolitan to noncore (nonmetropolitan). The classification scheme is recategorized into two broader categories for simplicity and ease of analysis: 1) Rural (Nonmetropolitan counties), which combines the micropolitan and noncore categories from the original classification, representing areas with lower population density and less urbanization; and 2) Urban (Metropolitan counties), which combines the large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan categories from the original classification, representing areas with higher population density and more urbanization. By recategorizing the classification scheme in this way, researchers can more easily compare health outcomes, access to healthcare services, and other factors between rural and urban areas in the United States.
Statistical Analysis
Descriptive statistics and chi-square analysis were used to describe and summarize all study variables and their associations with the study outcome, which was the total number of cancer cases (counts). Negative binomial regression models with Incidence Risk Ratios (IRR) were employed to examine the association between MHSVI themes and cancer incidence, as they are appropriate for count data with overdispersion.17 Both unadjusted and adjusted models were performed, accounting for covariates and county population weight. P-values ≤0.05 were considered statistically significant. All statistical analyses were conducted using STATA/MP version 17.0.18
Results
By employing a nationally representative sample and adjusting for potential confounders, our study offers valuable insights into the impact of social vulnerability on cancer disparities in the US. In this study, a total of 3,232 counties were analyzed, with an average of 2,817.9 (SD: 7,733.5) cancer cases, ranging from 16 to 201,547, and a total variance of approximately 59,800,000 (Table 1).
Impact of Minority Health Social Vulnerability on Cancer Incidence in the US, 2019
The MHSVI themes were evaluated for 2,920 counties, with a mean score of .5 (SD: .3), ranging from 0 to 1, and a variance of .1. The study population was divided into three groups based on overall MHSVI percentiles: low vulnerability (25.1%; n = 785), moderate vulnerability (49.3%; n = 1,539), and high vulnerability (25.6%; n = 801).
Regional distribution of the counties included the Midwest (33.6%; n = 1,055), Northeast (6.9%; n = 217), South (45.2%; n = 1,422), and West (14.3%; n = 448). Rural and urban classifications were also assessed, with 37.1% (n = 1,166) of the counties being urban and 62.9% (n = 1,976) being rural.
The unadjusted analysis of the impact of minority health social vulnerability on cancer incidence in the US showed significant associations between various MHSVI themes and cancer incidence. An increase in cancer cases was found for household composition (IRR: 1.15, 95% CI: 1.12-1.18, P<0.001) and medical vulnerability (IRR: 1.10, 95% CI: 1.08-1.14, P<0.001) themes. In the adjusted analysis of the impact of MHSVI themes on cancer incidence, the household composition theme showed a significant increase in cancer incidence, with an IRR of 1.19 (95% CI: 1.15-1.23, P<0.001). Comparing the overall MHSVI percentiles, the adjusted analysis reveals an increase in cancer incidence in both moderate (IRR: 0.94, 95% CI: 0.92-0.96, P<0.001) and high (IRR: 0.86, 95% CI: 0.84-0.88, P<0.001) MHSVI areas compared to low MHSVI areas. Regional differences were observed, with increased cancer incidence in the Northeast (IRR: 1.18, 95% CI: 1.15-1.22, P<0.001), South (IRR: 1.03, 95% CI: 1.01-1.05, P<0.001), and West (IRR: 0.92, 95% CI: 0.90-0.94, P<0.001) compared to the Midwest. Rural areas had a slight increase in cancer incidence compared to urban areas, with an IRR of 1.03 (95% CI: 1.01-1.04, P<0.001).
Discussion
Our study investigated the association between MHSVI and population-based cancer incidence across 3,232 counties in the US and its territories. The comprehensive use of the AHRQ SDOH database enabled us to examine various social determinants at the county level and their potential impact on cancer incidence nationwide. Our findings demonstrate that different MHSVI themes, MHSVI percentiles, and geographical factors are significantly associated with cancer incidence, highlighting the areas of importance in addressing SDOH to reduce cancer disparities. Furthermore, it establishes the utility and demonstrates the significance of MHSVI measures in oncologic research. There are prior reports of MHSVI indices and outcomes related to cancer treatments. To our knowledge, this is the first study to utilize a large, nationally representative sample to investigate the relationship between MHSVI and population-based cancer incidence.
Our study found the household composition and medical vulnerability themes demonstrated increased cancer incidence rates. These findings align with previous research that has identified associations between social determinants and cancer disparities.3,19 Our results emphasize the importance of addressing these social determinants to reduce cancer disparities. Furthermore, when examining overall MHSVI percentiles, our study showed both moderate and high MHSVI areas had increased cancer incidence compared to low MHSVI areas. This result is consistent with previous research, which has demonstrated that areas with higher social vulnerability are associated with higher cancer incidence rates.20,21 These findings suggest targeted interventions in areas with higher MHSVI may help reduce disparities in cancer outcomes.
The geographical variance was seen in cancer incidence, with increased incidence observed in the Northeast, South, and West compared to the Midwest. Additionally, rural areas exhibited a slight increase in cancer incidence compared to urban areas. These findings align with prior studies that have reported regional and rural-urban differences in cancer incidence.22,23 This highlights the need for tailored interventions to address the unique challenges faced by different regions and populations.
Our study adds to the growing body of literature on cancer disparities by providing a comprehensive analysis of the impact of MHSVI themes on cancer incidence. This information can be used by policymakers, healthcare providers, and researchers to develop targeted interventions to address the social determinants and reduce cancer disparities. Further research is needed to investigate the underlying mechanisms driving these associations and to evaluate the effectiveness of interventions aimed at addressing the identified disparities.
Implications for Research, Policy, and Clinical Practice
In terms of research, future studies should focus on employing longitudinal designs to better understand the causal relationships between MHSVI themes and cancer incidence. Longitudinal and multidimensional analysis is crucial for providing a comprehensive understanding of the relationship between MHSVI themes and cancer incidence by investigating individual and county-level factors.24,25 Additionally, examining the relationship between MHSVI themes and specific cancer types will help identify potential variations in their associations and inform strategies to reduce disparities in cancer outcomes.26
Policies should focus on improving socioeconomic conditions, enhancing healthcare infrastructure and access, and promoting culturally competent care. Addressing socioeconomic factors such as income, employment, and education in areas with high MHSVI scores can help reduce cancer disparities by increasing access to healthcare and preventive services.27 Policymakers should prioritize the development and expansion of healthcare infrastructure in areas with high MHSVI scores, particularly in rural and underserved communities.28 Culturally competent care, including increased training for healthcare providers, is essential for addressing the needs of diverse populations and reducing disparities in access to care and cancer outcomes.29
Clinical practice should emphasize screenings and early detection, patient navigation, and community outreach and education. Healthcare providers should stress the importance of regular cancer screenings and early detection in communities with high MHSVI scores.30 Implementing patient navigation programs can help address barriers to care and improve access to care, adherence to treatment, and overall cancer outcomes.31 Healthcare providers should engage in community outreach and education efforts, particularly in areas with high MHSVI scores, to increase awareness of cancer prevention and control measures, including providing information on risk factors, screening guidelines, and available resources to support cancer prevention and treatment.32
Study Strengths and Limitations
The strengths of our study include the use of a nationally representative sample, the examination of various dimensions of social vulnerability, and the employment of rigorous statistical methods. The AHRQ SDOH database allowed us to utilize a comprehensive data source that captures various social determinants affecting health outcomes and access to healthcare services in communities nationwide. The use of MHSVI, a composite measure of social vulnerability, enabled us to capture multiple dimensions of vulnerability that can potentially influence cancer disparities. Furthermore, the employment of negative binomial regression models provided an appropriate statistical approach for analyzing count data with overdispersion.
Despite its strengths, our study has some limitations. First, the cross-sectional design precludes causal inferences between MHSVI and cancer incidence. Future research using longitudinal data could provide more robust evidence of the causal relationship between social vulnerability and cancer disparities. Second, the use of county-level data may not capture finer-grained variations in social determinants and cancer incidence within counties. It is important to note our study was limited by the nature of the ecological data available through the AHRQ SDOH database, which only provides aggregated data at the county level. As a result, we were unable to collect or analyze intra-county prevalence of cancer or differentiate between types of cancer. Additionally, variables related to religion, spirituality, and culture were not included in this dataset. These limitations restrict the granularity of our findings and underscore the need for future research to incorporate these factors. Future studies should seek to include more detailed data on cancer prevalence, cancer types, and socio-cultural factors to better elucidate the complex relationships between social vulnerability and cancer incidence. Future studies incorporating data at smaller geographic scales, such as zip codes or census tracts, could provide a more nuanced understanding of the relationship between MHSVI and cancer disparities. Additionally, county-level data were not available for Kansas and Minnesota, which may limit the generalizability of our findings.
Conclusion
Our study highlights the significance of addressing social determinants of health to reduce cancer disparities. By examining the association between MHSVI and population-based cancer incidence in the US, we provide valuable insights for researchers, policymakers, and public health professionals to better understand and address the impact of social vulnerability on cancer disparities. Our findings underscore the need for targeted interventions to address the unique challenges faced by minority populations and other vulnerable groups, ultimately contributing to the reduction of health disparities and the promotion of health equity.
Acknowledgments
We would like to thank the American Society of Clinical Oncology for publishing our preliminary findings in the 2023 ASCO Annual Meeting Abstract in the Journal of Clinical Oncology: https://doi.org/10.1200/JCO.2023.41.16_suppl.e22501. We also acknowledge the Patient-Centered Outcomes Research Trust Fund and the Agency for Healthcare Research and Quality for the SDOH database that made it simpler to identify a variety of well-documented, linkable social determinant variables across domains without having to access multiple source files, thereby facilitating our research and analysis.
Footnotes
Author Contributions
Conception and design: Abdul Shour, Amog Jayarangaiah, Ronald Anguzu, David Puthoff, Adedayo A. Onitilo. Data analysis and interpretation: Abdul Shour, Amog Jayarangaiah, Ronald Anguzu, David Puthoff, Adedayo A. Onitilo. Manuscript writing: Abdul Shour, Amog Jayarangaiah, Ronald Anguzu, David Puthoff, Adedayo A. Onitilo. Financial support: Adedayo A. Onitilo. Administrative support: Adedayo A. Onitilo, Abdul Shour. Collection and assembly of data: Abdul Shour, Amog Jayarangaiah, Ronald Anguzu, David Puthoff, Adedayo A. Onitilo
- Received June 6, 2023.
- Revision received August 23, 2024.
- Accepted September 11, 2024.
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