Sage Journals: Discover world-class research

Abstract

Introduction

This study aimed to characterize the association between state and local social spending and incidence and mortality of poverty-associated cancers.

Methods

This cross-sectional cohort study (years 2004-2020) included U.S. adults ages 20-64 years with poverty-associated cancers. The exposure was differential and combined state- and local-level spending on social needs for 50 states. Data from the U.S. Census Bureau Census of Governments was used to determine annual social spending for each state. Deciles of spending were calculated annually. Main outcomes were yearly incidence and mortality of poverty-associated cancers, expressed as rate ratios where the first decile serves as the reference for each of deciles 2-10. Poisson regression models evaluated association of social spending with incidence and mortality of poverty-associated cancers, controlling for secular trends and state fixed effects.

Results

Overall median social spending was $7071dollars per capita (IQR $6373-$8098). By combined state/local social spending, yearly cancer incidence rates were lower in the highest deciles of social spending (rate ratio 0.96 (95% CI 0.92-0.99) and 0.92 (95% CI 0.88-0.96) for 9^th and 10^th deciles, respectively). Similarly, yearly cancer mortality rates were lower in the highest deciles of social spending (rate ratio 0.94 (95% CI 0.89-0.98) and 0.91 (95% CI 0.85-0.97) for 9^th and 10^th deciles, respectively).

Conclusion

This work demonstrates an association between state and local social spending and decreased incidence and mortality of poverty-associated cancers. These results can inform policies promoting spending on interventions that not only address general welfare but have downstream impacts on cancer risk and outcomes.

Keywords

cancer incidence cancer mortality social spending social drivers

Introduction

The United States (U.S.) spends more money on downstream treatment of cancer, such as targeted immunotherapies and radiation regimens, than any other country¹ despite the fact that upstream factors, such as social drivers of health, impact over 50% of U.S. cancer outcomes.^2-6 Specific governmental policies, regulations, and funding shape the social environment in which people live and thus their health, including risk and outcomes of diseases such as cancer.⁷ Prior work has demonstrated a correlation between social risk factors and incidence of certain cancers as well as cancer survival.^2,8 In a 2014 study of cancers of 39 different anatomic locations, 14 cancer sites were found to be associated with higher poverty at the census tract level in the U.S., including common and morbid cancers such as lung and colorectal cancer.⁸ In general, these poverty-associated cancers also correlate with behavioral risk factors such as tobacco and other substance use, sexual transmission, and poor diet.⁸ Notably, the combined categories of HPV-associated and tobacco-associated cancers show a positive association with poverty.⁸

Increases in specific domains of social spending have proven successful in reducing behavioral risk factors for malignancy. For example, it is well established that access to stable housing through needs-based rental assistance reduces food insecurity and lifts individuals and families out of poverty.⁹ Furthermore, spending on education and community development initiatives have been shown to reduce risky drinking behavior and decrease rates of tobacco use.^10,11 If geographic areas with high rates of social deprivation have a higher incidence of certain cancers and mortality from those cancers, it would follow that spending on interventions and infrastructure addressing that social deprivation may influence cancer incidence and outcomes. Thus, evaluation of spending at the state and local level and cancer outcomes is necessary. While some spending at the state and local level does target these upstream factors, the amount varies greatly.

Despite the persistent evidence linking social drivers to cancer incidence and outcomes, significant gaps in knowledge exist regarding how social spending at the state and local level influences the incidence and mortality of cancers in the United States. If higher public spending on these social drivers decreases their severity or impact on communities, one may expect correspondingly lower incidence of and mortality from poverty-associated cancers. This study aims to characterize the association between state and local social spending and the incidence and mortality of these select cancers previously demonstrated to be associated with poverty.

Methods

The reporting of this study conforms to the relevant RECORD guidelines.¹² This study was deemed exempt from ethics approval with waiver of informed consent by the Dartmouth Health Institutional Review Board given the de-identified nature of the publicly available data.

Cohort Determination

This cross-sectional cohort study evaluated annual state incidence and mortality of 14 cancer sites most strongly associated with residence in higher-poverty neighborhood.⁸ We specifically evaluated incidence and mortality rates for non-elderly adult patients, 20 to 64 years of age. Elderly adults ages 65 years and older were not included because they generally have greater access to social supports and safety nets, such as Medicare coverage and social security benefits, which are federally administered with little variance in access between states.^13,14 Non-elderly adults do not usually qualify for those national programs and thus are more likely to be affected by variations in social spending at the state and local level.^14,15,16

Exposure Variables

The exposure was combined state- and local-level spending on social needs. Data from the U.S. Census Bureau Census of Governments was used to determine annual state and local social spending for each state in years 2004-2020.¹⁷ The combined state and local expenditures was chosen because of considerable interstate variation in the definition of “local spending,” which sometimes represents town or county level spending and other times represents city or school district spending. Due to variability in which level of government provides different services, aggregation of state expenditures with spending at the various “local” levels enables meaningful comparisons across states. The individual expenditure categories that were combined under the social spending definition used in this study were: total assistance individual subsidies, total elementary and secondary education, total public health, total highways, housing and community development, libraries, parks and recreation, public welfare, and sanitation and sewage.¹⁸ Deciles of social spending were then determined at the annual basis. Deciles were chosen as a measure to elicit a more nuanced characterization of the relationship between exposure and outcomes, including any potential nonlinear relationship between spending and outcomes. Spending values are reported as dollars per capita and inflation adjusted to 2021dollars.

Outcomes

Primary outcomes were state-level yearly incidence of poverty-associated cancers and mortality from those cancers in years 2004-2020. Poverty-associated cancers were chosen because they include common and morbid cancers such as colorectal, liver, cervical, lung, larynx, oral cavity and pharynx, esophagus, and stomach cancers.⁸ Moreover, given their association with poverty, it may follow that spending channeled toward social drivers of health is more likely to impact their incidence compared to other cancers.

Cancer incidence and mortality data along with population estimates were obtained from the Center for Disease Control and Prevention (CDC) Wonder online databases for Cancer Incidence and Mortality.¹⁹ The CDC Wonder database includes data from statewide and metropolitan area cancer registries determined to meet quality criteria.²⁰ CDC Wonder uses International Classification of Diseases for Oncology, Third Edition (ICD-O-3) codes to categorize patients into standard groups of primary cancer sites according to the National Cancer Institute’s revised Surveillance, Epidemiology, and End Results Program (SEER) recodes.²⁰ Primary cancer sites were then chosen for analysis based on whether they have been found to be associated with poverty.⁸ Incidence and mortality are reported as case counts while also providing the age-adjusted total population estimates.

Statistical Analysis

To characterize trends in incidence of poverty-associated cancers and mortality from those cancers, the age-adjusted incidence and mortality rates were examined by state poverty rate level at the annual national decile. Age-adjusted incidence and mortality rates of poverty-associated cancers were also evaluated over time, from 2004 through 2020. Yearly incidence and mortality rates were then plotted along with median state and local social and public health spending in U.S. Dollars per capita.

To measure association, Poisson regression models were used to determine incidence and mortality rate ratios based on deciles of combined state- and local-level spending on social needs. The first decile of social spending serves as the reference group for each of the individual deciles 2-10. The models controlled for state fixed effects and year, with standard errors clustered at the state level. Models for mortality also accounted for age-adjusted incidence rates. Results were deemed significant with P-values ≤0.05 and with 95% confidence intervals (CI) that do not include 1.0.

Sensitivity analyses were performed (1) excluding state fixed effects, (2) excluding the year 2020 given its pandemic-related lower incidence rates, (3) incorporating temporal spending lags of 1 and 2 years into the model, (4) controlling for continuous state-level poverty rates, and (5) stratifying by state-level high vs low poverty rates. High poverty was defined as the top quartile of state poverty rate in the country, and low poverty was defined as the lower three quartiles of poverty rate. Analyses were performed using Stata Version 18.0 (College Station, TX). This study was deemed exempt from review by the Dartmouth Health Institutional Review Board.

Results

Trends in Cancer Incidence and Mortality Rates, by State Poverty Rate and Over Time

The poverty-associated cancers included in the study along with their overall incidence counts, age-adjusted incidence rates, mortality counts, and age-adjusted mortality rates are shown in Supplemental Table 1. When age-adjusted incidence of poverty-associated cancers and age-adjusted mortality from those cancers were examined by state poverty rate level at the annual national decile, both cancer incidence and mortality rates increased with higher poverty rate (Figure 1). Specifically, the age-adjusted cancer incidence rate rose from 84.6 cases per 100 000 in states with the lowest poverty rates to 109.0 cases per 100 000 in states with the highest poverty rates. Similarly, the age-adjusted cancer mortality rate also rose from 31.7 deaths per 100 000 in states with the lowest poverty rates to 46.6 deaths per 100 000 in states with the highest poverty rates.

Figure 1.

Association Between State Poverty Rates and Age-Adjusted Incidence and Mortality Rates for Poverty-Associated Cancers

When overall age-adjusted incidence of poverty-associated cancers and overall age-adjusted mortality from those cancers were evaluated over time alongside median state and local social and public health spending, three trends were apparent (Figure 2). Over time, the incidence of poverty-associated cancers has decreased, from 99.5 cases per 100 000 in 2004 to 83.7 cases per 100 000 in 2020. A similar trend was seen in overall age-adjusted mortality from poverty-associated cancers, with a decrease from 43.5 deaths per 100 000 in 2004 to 31.9 deaths per 100 000 in 2020. Over this same period, the median amount of state and local social spending increased, from $6845 per capita in 2004 to $8384 per capita in 2020.

Figure 2.

Trends in State and Local Social/Public Health Spending, Poverty-Associated Incidence Rates, and Poverty-Associated Mortality Rates Over Time

Characteristics of State and Local Social Spending

From 2004-2020, the overall annual median social spending in dollars per capita was $7071 (interquartile range, IQR $6373-$8098). The two largest components of spending were education ($3340; IQR $3020-$3658) and public welfare ($1797; IQR $1508-$2333), which together made up nearly three quarters of overall social spending (Table 1). The two smallest categories of social spending were libraries ($42; IQR $31-$54) and parks and recreation ($135; $101-$191).

Table 1.

Median Social Spending, Overall and by Individual Components

Component	Social spending^a median (IQR)
Overall	7071.00 (6373.00 – 8098.00)
Total assistance and individual subsidies	165.00 (126.00 – 231.00)
Total elementary and secondary education	3340.00 (3020.00 – 3658.00
Total public health	283.00 (207.00 – 392.00)
Total highways	640.00 (538.00 – 800.00)
Housing and community development	152.00 (113.00 – 215.00)
Libraries	42.00 (31.00 – 54.00)
Parks and recreation	135.00 (101.00 – 191.00)
Public welfare	1797.00 (1508.00 – 2333.00)
Sanitation and sewage	255.00 (214.00 – 311.00)

^aDollars per capita.

Association Between Social Spending and Cancer Incidence and Mortality

We evaluated the association between social spending and the incidence and mortality of cancer, controlling for secular trends, state fixed effects, and clustered standard errors at the level of the state. The yearly cancer incidence was lower for areas with the highest deciles of social spending, with incidence rate ratios of 0.96 (95% CI 0.92-0.99) and 0.92 (95% CI 0.88-0.96) for 9^th and 10^th deciles, respectively, whereas incidence rate ratios for areas with lower social spending ranged from 0.98 (95% CI 0.94-1.02) to 1.00 (95% CI 0.99-1.03) (Figure 3A). Similarly, yearly cancer mortality was lower for areas with the highest deciles of social spending, with mortality rate ratios of 0.95 (95% CI 0.90-0.99), 0.94 (95% CI 0.89-0.98), and 0.91 (95% CI 0.85-0.97) for the 8^th, 9^th, and 10^th deciles, respectively. Mortality rate ratios for areas with lower social spending ranged from 0.98 (95% CI 0.94-1.00) to 1.00 (95% CI 0.98-1.03) (Figure 3B).

Figure 3.

Association Between Social/Public Health Spending and the (a) Incidence and (b) Mortality of Poverty-Associated Cancer

Sensitivity Analyses

Sensitivity models excluding state fixed effects were consistent with primary models with state fixed effects. Results of sensitivity analysis excluding the year 2020 given its pandemic-related lower incidence rates did not differ significantly from primary analyses. Models employing temporal spending lags of 1 and 2 years were also consistent with primary models. Additionally, when the models controlled for state-level poverty rates or stratified by high vs low poverty rates, the highest deciles of social spending remained associated with lower yearly cancer incidence (Figure 4) and mortality (Figure 5).

Figure 4.

Association Between Social/Public Health Spending and the Incidence Rate of Poverty-Associated Cancer in (a) Lower Poverty and (b) High Poverty States (Lower Poverty = States in Lower Three Quartiles of Poverty Rate in Country; High Poverty = States in Top Quartile of Poverty Rate in Country)

Figure 5.

Association Between Social/Public Health Spending and the Mortality Rate of Poverty-Associated Cancer in (a) Lower Poverty and (b) High Poverty States (Lower Poverty = States in Lower Three Quartiles of Poverty Rate in Country; High Poverty = States in Top Quartile of Poverty Rate in Country)

Discussion

The findings of this work suggest an association between higher amounts of state and local social spending and decreased incidence of poverty-associated cancers, as well as decreased mortality for these common and morbid cancers. The association was only present in state-years with the highest levels of social spending. These results held true when controlling for state-level poverty rates or stratifying by poverty rates. The synchronous trends of increasing overall amount of social spending and decreasing incidence and mortality of poverty-associated cancers are worth noting; however, many possible confounding factors are likely at play, from developments in cancer treatment to other causes of death such as the opioid epidemic.

It must be noted that the full impact of changes in social spending on health outcomes such as cancer incidence and mortality may take time to become evident in a population.²¹ Cancers develop due to a complex interplay of biological and social factors. Additionally, larger societal and economic trends at any given time may offset the potential benefits of increased social spending, further delaying detection of improved health outcomes. For instance, our results show an increase in social spending around 2010 without a corresponding decrease in cancer incidence or mortality that year. The financial crisis of 2009-2010 may have also contributed to this discrepancy. The acute spike in unemployment and increased cost of living prompted increased social spending at the state and federal levels, but increased financial stress on individuals and communities may have counteracted the spending increases. This may help explain static rates of cancer incidence and mortality in these years, in conjunction with potential temporal lag in benefits, highlighting the importance of ongoing evaluation of this association over time.

The drivers behind the association between higher levels of social spending and decreased cancer incidence and mortality are likely multiple. Nearly three quarters of state and local social spending goes toward education and public welfare. Many of the poverty-associated cancers included in this analysis have either human papillomavirus (HPV), tobacco use, or alcohol use as risk factors for their development. Access to educational and community development programs have been shown to increase rates of HPV vaccination and decrease likelihood of behaviors such as smoking and alcohol misuse.^{10,11,22,23-28} It would follow that state and local public spending geared toward influencing the behaviors of individuals in a community can also impact development of certain cancers in those individuals down the road. Additionally, environmental conditions such as air pollution can influence the aggressiveness of cancer pathologies and thus impact cancer mortality.^29-32 Social spending geared toward improving environmental conditions may mitigate that impact. In another example, some social spending may reduce chronic stress due to financial hardship or multi-level racism which impairs the immune system’s ability to respond to malignant cells and hampers an individual’s ability to endure cancer treatment regimens.^33-35 Spending on infrastructure such as highways and transportation facilitates access to care for a community, which also may impact success of treatment and overall survival.^36-38 Public health spending and assistance programs may also address other barriers to health and health care such as housing instability or food insecurity.^39-43

Importantly, our sensitivity analyses suggest a possible threshold effect at play in states with the highest poverty rates, where only the highest decile of social spending is associated with reductions in cancer incidence and mortality. This may indicate that, in the most disadvantaged neighborhoods, only large-scale social investments will yield meaningful health impacts. Alternatively, the magnitude of the incident rate ratio in the 10^th decile may represent the relatively small numbers of observations in high poverty states within the highest decile of social spending. Additional econometric evaluation of potential threshold effects is warranted in future studies. However, the stratified analyses, each of which also control for state fixed-effects, provide stronger data that association between social spending and cancer outcomes is not a spurious correlation more closely related to state poverty-levels.

Our results align with prior work demonstrating that higher amounts of public assistance expenditures are associated with improved 6-year overall survival among adults with cancer.⁴⁴ While some work has found no association between social spending and overall cancer mortality^45,46 another more recent study evaluating state public assistance spending—including cash assistance and Medicaid—found an association with such programs and improved survival among cancer patients, both overall and for non-Hispanic Black and non-Hispanic White subgroups.⁴⁴ Our study goes further to demonstrate a relationship between public assistance spending and cancer incidence. Maclellan et al found a similar relationship in the Canadian setting, where they demonstrated a significant association between a higher social-to-medical spending ratio and lower incidence of colorectal, breast, and prostate cancer.⁴⁷ These results speak to the benefits of government spending that addresses upstream factors as a strategy to reduce disparities in cancer care and improve population-level cancer outcomes.

Limitations

Limitations of this study include its retrospective nature and the inability to control for multiple potential confounders. In particular, this analysis looks at a snapshot of time, assigning individuals to a state based on where they lived at the time of their cancer diagnosis. The factors leading to cancer development as well as to poor outcomes are often at play many years prior to diagnosis, and this analysis does not account for whether individuals previously lived in the same state vs elsewhere. Similarly, limitations in consistently captured spending and cancer data prevented evaluation of greater lags between spending and changes in outcome measures. However, models using one- and 2-year lags were consistent with primary findings. While this analysis accounts for state fixed effects, there are many other factors that could contribute to these findings, including state-level variations in overall population health not captured with fixed effects. Lastly, this study of poverty-associated cancers as a whole would not capture any differing associations between social spending and individual cancers. However, separate analyses of each cancer site were intentionally not performed so as to avoid the increased risk of Type I error due to multiple comparison testing.

Future research should examine the components of social spending to understand which targets are most impactful on cancer incidence and outcomes, which would help inform meaningful changes in policy and spending allocation. Studies comparing changes in cancer incidence and outcomes with changes in social spending policies over time may help confirm the associations observed in this study. Such natural experiments may provide more specific and targeted policy levers to influence prevention and survival of cancer. Additionally, social spending may or may not have a significant impact on the incidence and mortality of other cancer sites not included in this analysis, such as more highly prevalent cancers of the breast, prostate, and thyroid. Yet these malignancies are more prevalent in areas of lower poverty with potentially less need for public support to impact environment, resources, and behavior. Finally, social spending is likely disproportionate in its ability to influence the upstream drivers of cancer outcomes, like the social drivers of health and access to treatment, while having less of an influence on more downstream drivers like interpersonal racism, communication gaps, or variation in care between hospitals or cancer centers.⁴⁸

Conclusions

While increasing amounts of government policy and public health interventions are geared toward addressing social drivers of health, there remains a paucity of evidence connecting those interventions with concrete outcomes such as cancer incidence and survival. This study demonstrates a significant association between state and local social spending and decreased incidence of poverty-associated cancers as well as decreased mortality for individuals with those cancers. Future research will need to incorporate more granular spending and geographic data, such as specific interventions at the community level, as well as more nuanced patient-level cancer data such as tumor size and stage at diagnosis. This research can inform state and local social spending that addresses not only general welfare but may have downstream impacts on cancer incidence and mortality.

Supplemental Material

Supplemental material - Association of State and Local Social and Public Health Spending With Cancer Incidence and Mortality

Supplemental material for Association of State and Local Social and Public Health Spending With Cancer Incidence and Mortality by Laura E. Newton, MD, Kacie L. Dragan, PhD, Lucas Cusimano, Andrew P. Loehrer, MD, MPH in Cancer Control

Footnotes

Author Note

Presented in September 2024 at the 105^th New England Surgical Society Annual Meeting in Burlington, VT, where it was awarded the podium prize.

ORCID iDs

Laura E. Newton

Lucas D. Cusimano

Ethical Considerations

This study was deemed exempt from ethics approval with waiver of informed consent by the Dartmouth Health Institutional Review Board given the de-identified nature of the publicly available data.

Author Contributions

Laura Newton: research concept/design, data interpretation, drafting abstract, drafting manuscript, and critical revisions of manuscript. Kacie Dragan: research design, data interpretation, and critical revisions of manuscript. Lucas Cusimano: research design, data interpretation, and critical revisions of manuscript. Andrew Loehrer: research concept/design, data analysis and interpretation, statistics, drafting manuscript, critical revisions of manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by salary funding of author Laura Newton MD from the Veterans Health Affairs. The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Veterans Affairs, nor does the mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Research reported in this publication was also supported in part by the National Cancer Institute of the National Institutes of Health under award number K08CA263546 (APL).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data reported in this study are publicly available from Centers for Disease Control and Prevention (CDC) Wonder database (https://wonder.cdc.gov). and publicly requestable from the National Cancer Institute (NCI) SEER database. (). The interpretation and reporting of these data and the views expressed in this article are the responsibility of the authors and do not necessarily reflect the position or policy of the CDC, the NCI, or the U.S. Government.

Supplemental Material

Supplemental material for this article is available online.

Appendix

References

Chow

Bradley

Gross

. Comparison of cancer-related spending and mortality rates in the US vs 21 high-income countries. JAMA Health Forum. 2022;3(5):e221229. doi:10.1001/jamahealthforum.2022.1229

Banegas

Dickerson

Zheng

, et al. Association of social risk factors with mortality among US adults with a new cancer diagnosis. JAMA Netw Open. 2022;5(9):e2233009. doi:10.1001/jamanetworkopen.2022.33009

Yabroff

Han

Song

, et al. Association of medical financial hardship and mortality among cancer survivors in the United States. J Natl Cancer Inst. 2022;114(6):863-870. doi:10.1093/jnci/djac044

Ramsey

Bansal

Fedorenko

, et al. Financial insolvency as a risk factor for early mortality among patients with cancer. J Clin Oncol. 2016;34(9):980-986. doi:10.1200/JCO.2015.64.6620

Nolte

McKee

. In amenable mortality-deaths avoidable through health care-progress in the US lags that of three European countries. Health Aff. 2012;31(9):2114-2122. doi:10.1377/hlthaff.2011.0851

Coleman

Quaresma

Berrino

, et al. Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol. 2008;9(8):730-756. doi:10.1016/S1470-2045(08)70179-7

Kim

. The associations between US state and local social spending, income inequality, and individual all-cause and cause-specific mortality: the national longitudinal mortality study. Prev Med. 2016;84:62-68. doi:10.1016/j.ypmed.2015.11.013

Boscoe

Johnson

Sherman

Stinchcomb

Lin

Henry

. The relationship between area poverty rate and site-specific cancer incidence in the United States. Cancer. 2014;120(14):2191-2198. doi:10.1002/cncr.28632

Fischer

. Rental Assistance Reduces Hardship, Promotes Children’s Long-Term Success. Center on Budget and Policy Priorities; 2016.

10.

Murphy

Ollerenshaw

. A community-wide approach to reducing risky drinking cultures in young people in rural Australia. Aust J Rural Health. 2023;31(2):204-217. doi:10.1111/ajr.12936

11.

Khan

MSR

Putthinun

Watanapongvanich

Yuktadatta

Uddin

Kadoya

. Do financial literacy and financial education influence smoking behavior in the United States? Int J Environ Res Publ Health. 2021;18(5):2579. doi:10.3390/ijerph18052579

12.

Benchimol

Smeeth

Guttmann

, et al. The REporting of studies conducted using observational Routinely-collected health data (RECORD) statement. PLoS Med. 2015;12(10):e1001885. doi:10.1371/journal.pmed.1001885

13.

U.S. Census Bureau , “Percentage of people uninsured by age group: 2021 and 2022.

14.

Cohen

Cha

Terlizzi

Martinez

. Health insurance coverage: early release of estimates from the national health interview survey. In: SOURCE. National Center for Health Statistics; 2021.

15.

Social Security Administration . Sign up for medicare. https://www.ssa.gov/medicare/sign-up

16.

Inc. United Healthcare Services . Medicare eligibility: who qualifies for medicare coverage? https://www.uhc.com/medicare/medicare-education/medicare-eligibility

17.

US Census Bureau . Census of Governments Annual Survey: State and Local Finance Data. Urban Institute.

18.

Organisation for Economic Co-operation and Development . Indicators: social spending. https://www.oecd.org

19.

CDC Wonder . Cancer Incidence and Mortality Data. cdc.gov.

20.

U.S. Department of Health and Human Services . CDC wonder -- frequently asked questions. https://wonder.cdc.gov/wonder/help/faq.html

21.

Rubin

Taylor

Krapels

, et al. Are better health outcomes related to social expenditure? A cross-national empirical analysis of social expenditure and population health measures. doi:10.7249/rr1252

22.

Acampora

Grossi

Barbara

, et al. Increasing HPV Vaccination Uptake among Adolescents: A Systematic Review. Int J Environ Res Public Health. 2020;17(21):7997. doi:10.3390/ijerph17217997

23.

Sundstrom

Cartmell

White

Well

Pierce

Brandt

. Correcting HPV vaccination misinformation online: evaluating the HPV vaccination NOW social media campaign. Vaccines (Basel). 2021;9(4):352. doi:10.3390/vaccines9040352

24.

Hirth

. Disparities in HPV vaccination rates and HPV prevalence in the United States: a review of the literature. Hum Vaccines Immunother. 2019;15:146-155. doi:10.1080/21645515.2018.1512453

25.

Wallace

Paul

Gholizadeh

, et al. Neighborhood disadvantage and the sales of unhealthy products: alcohol, tobacco and unhealthy snack food. BMC Public Health. 2021;21(1):1361. doi:10.1186/s12889-021-11442-z

26.

Janssen

Mathijssen

van Bon-Martens

van Oers

Garretsen

. Effectiveness of alcohol prevention interventions based on the principles of social marketing: a systematic review. Subst Abuse Treat Prev Policy. 2013;8:18. doi:10.1186/1747-597X-8-18

27.

Schmengler

Peeters

Kunst

Oldehinkel

Vollebergh

WAM

. Educational level and alcohol use in adolescence and early adulthood—The role of social causation and health-related selection—The TRAILS study. PLoS One. 2022;17(1):e0261606. doi:10.1371/journal.pone.0261606

28.

McKenna

Slater

McCance

Bunting

Spiers

McElwee

. The role of stress, peer influence and education levels on the smoking behaviour of nurses. Int J Nurs Stud. 2003;40(4):359-366. doi:10.1016/S0020-7489(02)00099-8

29.

Jia

Gao

Zhang

Xiao

Zhang

Lam Yung

. Rapid increase in mortality attributable to PM2.5 exposure in India over 1998–2015. Chemosphere. 2021;269:128715. doi:10.1016/j.chemosphere.2020.128715

30.

Ashing

Jones

Bedell

Phillips

Erhunmwunsee

. Calling attention to the role of race-driven societal determinants of health on aggressive tumor biology: a focus on black Americans. JCO Oncol Pract. 2022;18(1):15-22. doi:10.1200/op.21.00297

31.

Erhunmwunsee

Wing

Shen

, et al. The association between polluted neighborhoods and TP53-mutated non–small cell lung cancer. Cancer Epidemiol Biomarkers Prev. 2021;30(8):1498-1505. doi:10.1158/1055-9965.EPI-20-1555

32.

Macedo-Perez

Gonzalez

Bornstein

Castellanos

Campos-Peralta

Jimenez-Fuentes

. P2.10-09 environmental pollution in the city of Mexico as a risk factor for lung cancer and its prognostic impact. J Thorac Oncol. 2019;14(10):S788. doi:10.1016/j.jtho.2019.08.1693

33.

Sridhar

Nguyen

Abushalha

, et al. Major stressful events and risk of developing head/neck and pancreatic cancer. J Clin Oncol. 2022;40(16):12128. doi:10.1200/jco.2022.40.16_suppl.12128

34.

Ellison

Coker

Hebert

Sanderson

Royal

Weinrich

. Psychosocial stress and prostate cancer: a theoretical model. Ethn Dis. 2001;11(3):484-495.

35.

Lord

Harris

Ambs

. The impact of social and environmental factors on cancer biology in black Americans. Cancer Causes Control. 2023;34:191-203. doi:10.1007/s10552-022-01664-w

36.

King

Chen

Dagher

Holt

Thomas

. Decomposing differences in medical care access among cancer survivors by race and ethnicity. Am J Med Qual. 2015;30(5):459-469. doi:10.1177/1062860614537676

37.

Charlton

Schlichting

Chioreso

Ward

Vikas

. 2015; Challenges of rural cancer care in the United States.

38.

Graboyes

Chaiyachati

Sisto Gall

Johnson

Krishnan

McManus

Thompson

Shulman

Yabroff

. Addressing Transportation Insecurity Among Patients With Cancer. J Natl Cancer Inst. 2022;114(12):1593-1600.

39.

Butler

Bowen Matthew

Cabello

. Re-balancing Medical and Social Spending to Promote Health: Increasing State Flexibility to Improve Health Through Housing. Brookings.

40.

Pérez

Wood

Patel

. The Plate Matters: Exploring the Intersection of Food Insecurity in Patients with Cancer. EMJ Oncology; 2023. doi:10.33590/emjoncol/10306925

41.

Azap

Woldesenbet

Akpunonu

, et al. The association of food insecurity and surgical outcomes among patients undergoing surgery for colorectal cancer. Dis Colon Rectum. 2024;67(4):577-586. doi:10.1097/DCR.0000000000003073

42.

Chinaemelum

Munir

Azap

, et al. Impact of food insecurity on outcomes following resection of hepatopancreaticobiliary cancer. Ann Surg Oncol. 2023;30(9):5365-5373. doi:10.1245/s10434-023-13723-w

43.

Gany

Melnic

, et al. Food to overcome outcomes disparities: a randomized controlled trial of food insecurity interventions to improve cancer outcomes. J Clin Oncol. 2022;2:3603-3612. doi:10.1200/JCO.21.02400

44.

Barnes

Johnston

Johnson

Chino

Osazuwa-Peters

. State public assistance spending and survival among adults with cancer. JAMA Netw Open. 2023;6(9):e2332353. doi:10.1001/jamanetworkopen.2023.32353

45.

Thorpe

Joski

. Association of social service spending, environmental quality, and health behaviors on health outcomes. Popul Health Manag. 2018;21(4):291-295. doi:10.1089/pop.2017.0136

46.

Bradley

Canavan

Rogan

, et al. Variation in health outcomes: the role of spending on social services, public health, and health care, 2000-09. Health Aff. 2016;35(5):760-768. doi:10.1377/hlthaff.2015.0814

47.

MacLellan

Kershaw

Kneebone

, et al. Chasing cancer: does the social-to-medical spending ratio relate to cancer incidence and mortality in Canadian provinces? A retrospective cohort study. BMJ Public Health. 2024;2(1):e000858. doi:10.1136/bmjph-2023-000858

48.

Loehrer

Green

Winkfield

, Inequity in cancer and cancer care delivery in the United States. 2024; doi:10.1016/j.hoc.2023.08.001

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.13 MB