Poverty Line Research Articles

Unveiling the influence of reproductive health on poverty: a cross-sectional study in Magwi County, South Sudan

Objective: To understand the relationship between household poverty and reproductive health characteristics in Magwi County, South Sudan. Background: Household poverty is a significant issue in many countries, including South Sudan. Poverty has been identified as a major obstacle to international development, affecting various aspects of development goals such as food security and health. Despite interventions by organizations like the World Bank, poverty rates in beneficiary countries like South Sudan have not seen significant reductions, suggesting the presence of predictors of poverty from behavioral, structural, and political origins. Methods: The study was conducted using an analytical cross-sectional survey design. The study targeted female and male spouses in households and employed a multistage sampling approach to select participants. Result: The results of the study revealed that the level of household poverty in Magwi County was 42%. The prevalence of household poverty was found to be influenced by reproductive health characteristics. The use of short-acting contraception by women was associated with a higher prevalence of poverty, whereas women who had ever aborted a pregnancy had a lower prevalence of poverty. Unintended pregnancy and inconsistent condom use by men were also associated with higher poverty rates, whereas men with only one sexual partner had lower poverty rates. Conclusion: This study provides valuable insights into the relationship between household reproductive health characteristics and poverty in Magwi County, South Sudan. It emphasizes the need for comprehensive approaches that address both behavioral and structural factors to effectively reduce poverty and improve development outcomes.

Impact of Poverty on Stroke Recurrence: A Population-Based Study.

Poverty is associated with greater stroke incidence. The relationship between poverty and stroke recurrence is less clear. In this population-based study, incident strokes within the Greater Cincinnati/Northern Kentucky region were ascertained during the 2015 study period and followed up for recurrence until December 31, 2018. The primary exposure was neighborhood socioeconomic status (nSES), defined by the percentage of households below the federal poverty line in each census tract in 4 categories (≤5%, >5%-10%, >10%-25%, >25%). Poisson regression models provided recurrence rate estimates per 100,000 residents using population data from the 2015 5-year American Community Survey, adjusting for age, sex, and race. In a secondary analysis, Cox models allowed for the inclusion of vascular risk factors in the assessment of recurrence risk by nSES among those with incident stroke. Of 2,125 patients with incident stroke, 245 had a recurrent stroke during the study period. Poorer nSES was associated with increased stroke recurrence, with rates of 12.5, 17.5, 25.4, and 29.9 per 100,000 in census tracts with ≤5%, >5%-10%, >10%-25%, and >25% below the poverty line, respectively (p < 0.01). The relative risk (95% CI) for recurrent stroke among Black vs White individuals was 2.54 (1.91-3.37) before adjusting for nSES, and 2.00 (1.47-2.74) after adjusting for nSES, a 35.1% decrease. In the secondary analysis, poorer nSES (HR 1.74, 95% CI 1.10-2.76 for lowest vs highest category) and Black race (HR 1.31, 95% CI 1.01-1.70) were both independently associated with recurrence risk, though neither retained significance after full adjustment. Age, diabetes, and left ventricular hypertrophy were associated with increased recurrence risk in fully adjusted models. Residents of poorer neighborhoods had a dose-dependent increase in stroke recurrence risk, and neighborhood poverty accounted for approximately one-third of the excess risk among Black individuals. These results highlight the importance of poverty, race, and the intersection of the 2 as potent drivers of stroke recurrence.

A Geospatial Analysis of Barriers to Cleft Lip and Palate Care in the United States.

This study evaluates the geospatial distribution of cleft lip and/or cleft palate (CL/P) care in the United States, assesses disparities between families with and without one-hour proximity to CL/P care, and recommends interventions for improving access. We identified American Cleft Palate Craniofacial Association-approved CL/P teams and calculated a one-hour driving radius around each clinic. We then used census data to compare risk factors for developing cleft (i.e., incidence risk factors) and obstacles to care (i.e., access risk factors) between counties with and without one-hour proximity. We identified 187 CL/P teams in 45 states. Most were in the South (n = 60, 32.0%), though children in the Middle Atlantic had the greatest access to care. Alabama, Mississippi, Tennessee, and Kentucky had the least access. Children without access were 39% more likely to have gestational tobacco exposure, 8% more likely to have gestational obesity exposure, and 28% less likely to have health insurance (p < 0.01). Children without access in the South were 29% more likely to have a low birth weight and 46% more likely to be living below the poverty line (p < 0.01). Children with access were twice as likely to live in immigrant families and 7-times more likely to speak English as a second language. Pronounced disparities affect patients with and without one-hour access to CL/P care. Interventions should address care costs for patients living furthest without access and language barriers for patients with access that speak English as a second language.

Investigation of geographic disparities of diabetes-related hospitalizations in Florida using flexible spatial scan statistics: An ecological study.

Hospitalizations due to diabetes complications are potentially preventable with effective management of the condition in the outpatient setting. Diabetes-related hospitalization (DRH) rates can provide valuable information about access, utilization, and efficacy of healthcare services. However, little is known about the local geographic distribution of DRH rates in Florida. Therefore, the objectives of this study were to investigate the geographic distribution of DRH rates at the ZIP code tabulation area (ZCTA) level in Florida, identify significant local clusters of high hospitalization rates, and describe characteristics of ZCTAs within the observed spatial clusters. Hospital discharge data from 2016 to 2019 were obtained from the Florida Agency for Health Care Administration through a Data Use Agreement with the Florida Department of Health. Raw and spatial empirical Bayes smoothed DRH rates were computed at the ZCTA level. High-rate DRH clusters were identified using Tango's flexible spatial scan statistic. Choropleth maps were used to display smoothed DRH rates and significant high-rate spatial clusters. Demographic, socioeconomic, and healthcare-related characteristics of cluster and non-cluster ZCTAs were compared using the Wilcoxon rank sum test for continuous variables and Chi-square test for categorical variables. There was a total of 554,133 diabetes-related hospitalizations during the study period. The statewide DRH rate was 8.5 per 1,000 person-years, but smoothed rates at the ZCTA level ranged from 0 to 101.9. A total of 24 significant high-rate spatial clusters were identified. High-rate clusters had a higher percentage of rural ZCTAs (60.9%) than non-cluster ZCTAs (41.8%). The median percent of non-Hispanic Black residents was significantly (p < 0.0001) higher in cluster ZCTAs than in non-cluster ZCTAs. Populations of cluster ZCTAs also had significantly (p < 0.0001) lower median income and educational attainment, and higher levels of unemployment and poverty compared to the rest of the state. In addition, median percent of the population with health insurance coverage and number of primary care physicians per capita were significantly (p < 0.0001) lower in cluster ZCTAs than in non-cluster ZCTAs. This study identified geographic disparities of DRH rates at the ZCTA level in Florida. The identification of high-rate DRH clusters provides useful information to guide resource allocation such that communities with the highest burdens are prioritized to reduce the observed disparities. Future research will investigate determinants of hospitalization rates to inform public health planning, resource allocation and interventions.

Who is Anaemic in India? Intersections of class, caste, and gender.

Anaemia severely impacts physical and mental abilities, raises health risks, and diminishes the quality of life and work capacity. It is a leading cause of adverse pregnancy outcomes and maternal mortality, especially in developing nations like India, where recent data on anaemia from National Family and Health Survey (NFHS-4) (2015-16) and NFHS-5 (2019-21) indicate a tremendous rise. Anaemia is a marker of poor nutrition and health, and socio-economic factors such as gender norms, race, income, and living conditions influence its impact. As a result, there are disparities in how anaemia affects different segments of society. However, existing research on health inequity and anaemia often employs a single-axis analytical framework of social power. These studies operate under the assumption that gender, economic class, ethnicity, and caste are inherently distinct and mutually exclusive categories and fail to provide a comprehensive understanding of anaemia prevalence. Therefore, the study has adopted the theoretical framework of intersectionality and analysed the NFHS-5 (2019-21) data using bivariate cross-tabulations and binary logistic regression models to understand how gender, class, caste, and place of residence are associated with the prevalence of anaemia. The results suggest that the women of Scheduled Tribes (ST) and Scheduled Castes (SC) share a disproportionate burden of anaemia. This study confirms that economic class and gender, geographical location, level of education, and body mass index significantly determine the prevalence of anaemia. The ST and SC women who are economically marginalised and reside in rural areas with high levels of poverty, exclusion, and poor nutritional status have a higher prevalence of anaemia than other population groups. Thus, the study suggests that intersections of multiple factors such as caste, class, gender, and place of residence significantly determine 'who is anaemic in India'.

Cleft Lip and Palate Surgery at a Rural African Hospital: A 13-Year Experience From Western Kenya.

Most studies on the treatment of cleft lip and palate (CLP) in low-income and middle-income countries have reported on the experience of urban centers or surgical mission trips to rural locations. There is a paucity of literature on the experience of local teams providing orofacial cleft surgery in rural Sub-Saharan Africa. This study reports the efficacy and cost-effectiveness of cleft surgery performed by an all-local team in rural Kenya. A retrospective chart review was performed on all patients who received CLP repair at Kapsowar Hospital between 2011 and 2023. Information regarding patient age, sex, cleft etiology, surgical management, and home location was retrieved. For the most recent year of study (2023), the authors performed a financial audit of all costs related to the performance of unilateral cleft lip surgery. Descriptive statistics were performed. The authors identified 381 CLP surgeries performed on 311 patients (197 male, 63.3%). The most common etiology of the cleft was left unilateral (28.3%). The average age of primary lip repair decreased from 46.3 months in 2008 to 2009 to 20.2 months in 2022 to 2023 (P<0.001). The average age of primary cleft palate repair decreased from 38.0 months in 2008 to 2009 to 25.3 months in 2022 to 2023 (P<0.001). Patients traveled from 23 districts to receive treatment. Age of treatment was not different when distinguished by sex, county poverty level, or travel time from the hospital. The total costs associated with cleft lip repair was $201.6. Adequately staffed hospitals in rural locations can meaningfully address a regional CLP backlog more cost-effectively than surgical mission trips.

Universalism versus residualism: a micro-simulation of alternative income maintenance schemes in South Korea

This article examines the past, present and future of income maintenance schemes in Korea. Historically, income security schemes have been built on the idea of work-centred social insurance supplemented by social assistance. This approach was based on the premise of full employment. While current schemes have achieved institutional completeness and have contributed to alleviating poverty and inequality, they have exhibited limitations in responding to the qualitative shifts of capitalism, leading to welfare blind spots. Various alternatives have been proposed, such as universal basic income (UBI), which aims for equality, and residual Safety Income (SI), which aims for efficiency. The objective of this study is to validate the effects of basic income proposals and SI as alternative income maintenance schemes emerging in Korea. We simulated and compared the poverty alleviation and income redistribution effects of the two alternatives using data from the Survey of Household Finances and Living Conditions (2019~2021). The effects of poverty alleviation and income distribution were determined by analysing the hypothetical changes in absolute and relative poverty rates, as well as the Gini coefficient. The efficiency of benefits was assessed as the ratio of the amount used to reduce the poverty gap out of the total benefit amount. The study found that while SI appeared cost-effective in addressing absolute poverty, UBI was also effective in addressing relative poverty and income inequality.

The influence of access to care on radiation therapy utilization among older women with breast cancer.

1539 Background: In 2004, the Cancer and Leukemia Group B (CALGB) C9343 trial compared outcomes among women aged ≥ 70 who had stage I, estrogen-receptor positive (ER+) breast cancer (BC) who received a lumpectomy and hormonal therapy, treated with and without radiation therapy (RT). While the trial found that overall survival was not different between groups, RT use did not significantly decline after its publication. We investigated regional variation in RT utilization in the United States (US) and its association to access to healthcare among women aged ≥ 70 diagnosed with localized ER+ BC after partial mastectomy (PM) between 2004–2020. We hypothesize that women with greater access to health care will more often receive RT. Methods: To examine regional variation in the use of RT and its association with access to healthcare, we extracted data from the Surveillance, Epidemiology, and End Results 17 registry. From 2004 – 2020, 105,694 women aged ≥ 70 years who received a PM for localized ER+ BC across 199 US counties with a population &gt; 50,000 were identified. Access to healthcare was measured using six socioeconomic (SES) variables: median household income, % with high school education, % of families above poverty line, % with bachelor’s degree, % speaking English, and % employed, measured from 2015-2019. A multivariable linear regression model tested for association between each variable and RT use. A composite SES score was calculated as the sum of z-scores across all six variables and we identified the top 20 and bottom 20 scoring counties. SES score was used as a surrogate for access to healthcare and was correlated to RT use using a linear regression model. Results: The percentage of women aged ≥ 70 receiving RT after PM for localized ER+ BC varied across counties from 19.0% to 84.6%. In 2004, receipt of RT was similar between the top 20 and bottom 20 counties (67.8% vs 65.2%, respectively). This decreased after publication of CALGB C9343; by 2020 receipt of RT was 58.7% for the top 20 and 49.2% for the bottom 20 SES counties (Table). In linear regression analysis, SES was significantly associated with RT use (p&lt;0.0001). In multivariable linear regression analysis, only % above high school education was significantly associated with RT use (p=0.0205). Conclusions: Among women aged ≥ 70 with localized ER+ BC who underwent PM and who were candidates for omission of RT, those who lived in higher SES counties were more likely to receive RT from 2004 – 2020. Since the CALGB C9343 trial in 2004, RT use has declined; however, the decline was less among those with higher SES and therefore likely less among those with greater access to healthcare. These women may experience over treatment, which may result in personal or system wide harms. [Table: see text]

Factors associated with delay in breast biopsy in a vulnerable population.

e13526 Background: Prompt diagnosis and treatment of breast cancer can improve outcomes and reduce stress and anxiety in patients. Race, socioeconomic status, and education level are associated with delays in diagnosis in breast cancer patients. 63% of Louisiana’s parishes are classified as rural, and 18.8% of the population is below the poverty line (the second highest in the country). The above factors make access to care challenging. Our study aimed to identify factors associated with delay in breast biopsy after abnormal diagnostic imaging in our patient population. Methods: A retrospective cohort study including female patients &gt;18 years undergoing breast biopsy for abnormal diagnostic imaging findings from 1/1/2022 to 12/31/2022 at LSU Health, Shreveport, was done. Patients with a prior history of breast cancer, pregnant females, and patients with cognitive defects were excluded. Patients were followed from abnormal diagnostic imaging to biopsy. Descriptive analysis was done for baseline cohort characteristics. Univariate and multivariate logistic regression models were used to find 95% Confidence Interval and Odds ratio (ORs) for independent factors associated with time to biopsy (TTB). The study was approved by IRB. Results: 148 women (mean age [SD]: 54 [12] years) were included in the analysis. 67.5% were African American, and 25.6% lived in rural areas. The mean distance from the patient’s home to our center was 26.7 miles (Range: 3-219). The mean TTB from abnormal diagnostic imaging was 13.79 days (Range: 0-84), and 67.5% of patients had TTB of =&lt;14 days. A TTB of more than 14 days was considered a delay in biopsy. After adjusting for age, multivariate logistic regression showed rural residence was associated with TTB of &gt;14 days. (OR: 2.5, 95% CI: 1.15-5.67, p=0.02) (Table). A distance more than 40 miles from the hospital was associated with a higher likelihood of TTB of &gt;14 days on a multivariate model adjusted for age and race revealed (OR: 2.2, 95% CI: 1.004-5.10, p= 0.04). Conclusions: Patients residing in rural parishes and at a distance more than 40 miles from our center have a higher likelihood of delay in time to biopsy from the diagnostic imaging. Same-day breast biopsy should be prioritized in such patients to ensure timely diagnosis and treatment. Cancer Centers serving the safety net population can conduct similar studies and implement changes to ensure equitable access to care. [Table: see text]

Effects of socioeconomic status (SES) and healthcare resource (HCR) availability on survival in Black patients (pts) versus (vs) White pts with multiple myeloma (MM): A SEER Medicare analysis.

e13678 Background: In MM, disparities exist for overall survival (OS) by race, and many factors may contribute to these differences. This study evaluates whether SES and HCR availability impacts OS in older pts with newly diagnosed MM (NDMM) based on race. Methods: This retrospective study used linked SEER-Medicare claims (diagnosis [Dx] 6/1/2013–12/31/2017) and Area Health Resource Files (AHRFs; from 2018) to identify non-Hispanic White and non-Hispanic Black pts aged ≥66 years with NDMM. AHRFs included county-level HCR availability data (e.g. number of long-term hospital beds, medical doctors [MDs]). Continuous Medicare A and B enrollment until 12/31/2019 or preceding death was required. Pts with other cancers, Dx from death data, missing county information and enrollment in health maintenance organizations or clinical trials were excluded. Kaplan-Meier was used for unadjusted median OS and Cox proportional hazards for OS risk by race. Age, sex, race, Charlson Comorbidity Index (CCI), poverty, education, and HCR availability were included in the adjusted mixed effects Cox model. Results: We identified 6,609 pts with NDMM; 15.6% were Black. For Black pts vs White pts, median age at Dx was 76 vs 77 years, 57.1% vs 46.0% were female, and mean CCI was 2.1 vs 1.4 (p&lt;.001 for all). Within census tracts, mean percentage of pts living under the poverty line and received &lt;12 years of education was 21.2% vs 11.3% (p&lt;.001) and 19.0% vs 11.3% (p&lt;.001) for Black pts vs White pts, respectively. Unadjusted median OS for Black pts vs White pts was 2.76 vs 3.01 years (hazard ratio [HR]: 1.08; p=.063). In the adjusted model, several SES and HCR availability factors were significant. OS HR by race reversed directionality when adjusted for demographics, SES and HCR availability, but this was not significant (HR: 0.92; p=.12; Table). Conclusions: We found that Black pts with NDMM in SEER-Medicare claims were younger, had higher CCI, completed less education, and were more likely to live in census tracts with higher poverty percentages vs White pts. Several factors relating to SES and HCR availability significantly influenced OS and may drive disparities in care. Further research on larger datasets is needed to better understand these disparities. [Table: see text]

Non-receipt of targeted and immunotherapies in diverse patients with metastatic cancers.

e13563 Background: The rapid evolution of molecularly targeted kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) in the treatment of metastatic cancer, coupled with high drug costs, raises potential for unwarranted variation in patient management. We evaluated correlates of non-receipt of TKIs and ICIs in a diverse, population-based sample of patients with metastatic non-small cell lung cancer (NSCLC), kidney and bladder (GU) cancer, and melanoma. Methods: We identified 2240 patients diagnosed in 2019 with metastatic NSCLC, GU cancer, or melanoma and reported to the Georgia or Los Angeles SEER registries. Using SEER registry data, we linked all patients to a managing oncology physician. We collected data from the managing physician regarding receipt of TKIs and ICIs. We used bivariate analyses and multivariable logistic regression models to assess associations between non-receipt of TKIs and ICIs and patient-level factors. Results: We present results for a preliminary sample (N=894). About half (55%) of the patients had NSCLC, 31% had GU cancer, and 14% had melanoma. The mean age was 62 (SD 12); 59% were male; 65% were White, 16% were Black, 11% were Hispanic, and 7% were Asian; 52% had Medicare, 29% had private insurance, 9% had Medicaid, and 4% had no insurance; 89% resided in urban areas, 11% resided in rural areas. 22% lived in a census tract area with ≥20% of the population living below the poverty level. The Table shows that in bivariate analyses, non-receipt of TKIs was associated with NSCLC, older age, male sex, non-white race, and non-private or no insurance (all p&lt;0.05). After adjustment, non-receipt of TKIs was associated with NSCLC, older age, male sex, and race. Asian and Hispanic patients had lower rates of non-receipt, and Black patients had higher rates. In bivariate analyses, non-receipt of ICIs was associated with NSCLC and GU cancer (p=0.004); this association remained significant after adjustment. Conclusions: Non-receipt of TKIs was associated with important non-clinical factors including race and sex. Non-receipt of ICIs was associated only with cancer type. These findings suggest that policy-relevant factors such as out-of-pocket costs for oral cancer therapies and differential access to molecular sequencing may contribute to unwarranted variation in receipt of TKIs. [Table: see text]

Access to and equity in cancer clinical trials in Oregon.

e23100 Background: Approximately 20,000 people per year are diagnosed with cancer in Oregon. The OHSU Knight Cancer Institute is the only academic cancer center in the state, with the nearest center located almost 200 miles away. Clinical trials (CT) are essential for cancer care but only a small proportion of eligible people participate due to multiple factors. In this retrospective study, we identified the association between sociodemographic factors and cancer CT participation at OHSU. Methods: Adult patients referred to OHSU for evaluation and treatment of a new cancer 2019-2022 were included. Data collected included age, gender, race/ethnicity, zipcode, insurance, type of cancer and CT participation. Zip-codes were used to estimate poverty level as defined by the American Community Survey, rural vs. urban location and distance to the cancer center. Multivariate analysis was conducted to identify factors associated with CT participation. Results: A total of 14,261 patients with median age 65 (18-101) years were treated at OHSU from 2019-2022 (86% for solid tumors, 14% hematologic malignancies). Of these, 53% were &gt; 65yrs, 51% male and 8.5% self-identified as non-White (including Hispanic). These numbers are similar to those reported in the statewide cancer registry. About 61% of those &lt; 65 yrs were privately insured, 84% of those &gt; 65 yrs had Medicare, and 31% were from areas at or below the national poverty level. About 40% lived &gt; 30 miles from OHSU (29% &gt; 60 miles, 14% &gt; 120 miles) and 31.5% lived in rural areas. A total of 2134 patients (15%) participated in cancer CT (8% interventional, 6% interventional therapeutic and 10% noninterventional). Factors independently associated with decreased CT participation on multivariate analysis included age &gt; 65yrs regardless of type of insurance, &lt; 65yrs with public insurance, female, racial/ethnic minority, solid tumor diagnosis and cancer care at a community-based clinic (Table 1). Conclusions: Patient with cancer treated at OHSU are representative of the population in our catchment area and region. However, there is room to improve access and CT participation for older adults and persons from racial/ethnic minorities and disadvantaged backgrounds. Our study highlights the importance of understanding the catchment area and accounting for social determinants of health when implementing community outreach strategies for CT participation. [Table: see text]

Ubuntu or Compliance? Knowledge, Attitudes, and Practices of Owners of Small- Medium-Sized Enterprises in Johannesburg, South Africa Regarding Corporate Social Responsibility

ABSTRACT There is a paucity of studies demonstrating how small and medium-sized enterprises (SMEs) adopt CSR interventions to enhance social and economic conditions of communities within which they operate. There is also a prevailing stereotype that Corporate Social Responsibility is only applicable to big, multinational companies. The study therefore explored the knowledge, attitudes, and practices of 10 owners of SMEs in Johannesburg, South Africa regarding CSR. Guided by a social development lens, the study adopted a qualitative case study research design. Thematic analysis of interview responses revealed that most of these owners considered their SMEs to be practising CSR, and were motivated primarily by the intrinsic spirit of Ubuntu rather than extrinsic compliance with regulatory requirements. While some CSR interventions (such as skills-transfers as empowerment) were found to be consistent with the social development approach, others, such as philanthropy, were not necessarily developmental but nevertheless important in a developing country such as South Africa with its high levels of poverty. The key contributions of the study to knowledge are first, that it debunks the misconception in the literature that SMEs are too small and financially incapable of implementing CSR interventions; and second, that it enhances understanding from a developing world perspective of the factors motivating SME owners to engage in CSR.

Disparities and outcomes of immune checkpoint inhibitor therapies in LMICs: Retrospective study on current state, efficacy, and challenges in Armenia.

e23315 Background: The escalating incidence of cancer in Armenia is a global trend, underscoring the urgency for innovative treatments, including immune checkpoint inhibitors (ICIs). This study, a first in the region, investigates ICIs' real-world impact, emphasizing the current state and critical gaps in access to care. Methods: We conducted a retrospective review of 224 patients, excluding 32, resulting in 192 patients treated with ICIs between 2017 and 2023 across four major oncology centres. The review covered demographic and clinical data, genetic testing, treatment regimens, and survival outcomes, analyzed using the STATA 18 BE. Results: The mean age of the patients was 61.4 years, with 69.27% being male. Lung cancer was the most common diagnosis (42.19%, n = 81), followed by melanoma (11.98%, n = 23) and gastric cancer (10.94%, n = 21). Survival outcomes varied, with melanoma patients exhibiting a mean overall survival (OS) of 33.26 months, lung cancer patients 19.69 months, and gastric cancer patients 20.50 months; the survival difference between patients with metastases and without was not statistically significant. Patients receiving ICIs in the second or later lines of treatment had a 2.12-fold lower chance of survival compared to those receiving them as first-line treatment (95% CI 1.16-3.88, p = 0.014). 78% of patients received ICIs in the metastatic setting and only 22% in curative. In two centres, among 185 patients with metastatic lung cancer, only 23.2% (43 patients) received ICIs, and of these, about 50% underwent mutation testing, with only 4 assessed via broad panel NGS. A significant 76.8% (142 patients) did not receive immunotherapy. Furthermore, 34% of those starting ICI treatment were forced to discontinue due to financial hardships. Pembrolizumab and Nivolumab were the most widely used agents, but the choice varies significantly between centres. Conclusions: The financial barrier is substantial: the cost of one pembro cycle on the black market, at $3,000, is 3.8 times the annual income of those at the national poverty line, more than twice the income of the lower middle-income class, and represents over 60% of the country's GDP per capita. Median cycle lengths for ICIs, such as 6.5 for Ipil+Nivo and 5.61 for Pembro, are below the NCCN's standard recommendations, highlighting the profound impact of financial constraints on treatment adherence and duration. This study reveals the stark reality of ICI accessibility and affordability in Armenia, where a significant portion of cancer patients are unable to benefit from these potentially life-extending treatments. Additionally, a preference bias towards selecting treatments without nationwide guidelines was observed, alongside the absence of a national E-health database, underscoring the need for policymaker attention, insurance adjustments, and more precise, prospective data collection.

Unveiling the interplay of social factors in cancer survivorship: A comprehensive social determinants of health (SDOH) profile analysis.

1536 Background: SDOHs contribute to patients’ cancer survivorship outcomes. While studies tend to focus on individual SDOH, understanding the interplay and collective impact of multiple SDOHs is vital for improving patient outcomes and access to care. Our study aims to understand SDOH profiles in cancer survivors and stratify social risks by analyzing relationships between SDOH profiles and health outcomes using a nationally representative dataset. Methods: We conducted an unsupervised clustering analysis using 2013-2018 National Health Interview Survey data, linked to NHIS Mortality Files, to examine 12 social determinants of health (SDOHs) in the general population. 12 SDOH included unmarried status, unemployment, less than high school education, material/psychological/behavioral financial hardship, transportation/food/housing insecurity, delayed care due to other reasons, and low income(less than federal poverty line), and low neighborhood cohesion. K-Modes clustering was used to identify optimal number of cluster. We estimated each cluster’s prevalence in younger (18-64 years) and older (65-79 years) cancer survivors, then used weighted Cox regression to assess the risk of overall (OS)in both age groups, adjusting for demographics. Results: We identified 5 distinct groups based their SDOH profiles, including group A (few SDOH barriers), B (unmarried but no other SDOH barriers), C (unemployed but no other SDOH barriers), D (unmarried, unemployed, occasionally having other SDOH barriers) and E (the highest rate of financial hardship/transportation/food/housing insecurity/low neighborhood cohesion/low income). Notably, group E, compared to all other groups, had the highest rate of racial minorities in both younger and older groups in both younger (71% vs 5-14%) and older populations (74% vs 1-8%). Older survivors in Group C (HR 2.48, 95% CI: 1.02-6.03), Group D (HR 4.09, 95% CI: 1.65-10.14), and Group E (HR 3.88, 95% CI: 1.44-10.46) had significantly lower OS rates compared to those in Group A. For younger survivors, Group D (HR 1.96, 95% CI: 0.97-3.96) and Group E (HR 1.40, 95% CI: 0.67-2.95) were associated with nonsignificant reductions in OS, possibly due to limited sample sizes. Conclusions: SDOHs form distinct clusters, each with profound on cancer survivorship especially among older survivors facing complex social challenges. This necessitates customized health interventions focused on these SDOH profiles, crucial for improving patient outcomes and addressing health disparities.

Dynamics of Ageing in Akoko Area of Ondo State Nigeria: Challenges of Public Welfare for the Aged

Objectives: The purpose of this study is to investigates the dynamics of ageing in Akoko Land of Ondo State Nigeria and challenges of public welfare for the aged. The Study was anchored on disengagement theory to explain the inevitable process of disengagement as a rewarding and universal that must be mutually agreed upon. Methods: Both quantitative and qualitative data were collected from randomly selected respondents and key informant participants numbering one hundred and forty (140). The quantitative data collected from 120 respondents were analyzed with statistical package for the social sciences, while the qualitative data collected from 20 participants were analyzed using content analysis. Results: Findings revealed that the aged were relatively neglected in term of care and social security. Majority of the respondents 94.2% agreed that extended family system alone cannot stand as a social insurance for the aged. 90% agreed that improvement in the social care and security policies across public and private organization would help to alleviate most aged poverty level. Conclusions: This study recommends, among others, that every family should extend mutual love and care gesture towards their ageing cohort, the aged should themselves engage in proper future savings and investments, while the society, through the non-governmental organizations (NGOs) and the Government should intensify their efforts to provide social security, public infrastructure, medical facility, prompt pension and retirement benefit payment in order to assure graceful ageing for every aged cohort in the society.

High deductible health plans and survival among cancer survivors.

11005 Background: High deductible health plans (HDHP) enable lower premiums at the expense of potentially high out-of-pocket costs. They are associated with more advanced cancer stage diagnoses and delayed or forgone care among cancer survivors. However, it is unknown how HDHPs are associated with survival among cancer survivors. Methods: Individuals ages 18-84 years with non-Medicaid insurance were identified from the 2011-2018 National Health Interview Survey (NHIS) with linked mortality files from the National Death Index. HDHP status was defined by the NHIS as a yearly deductible ≥$1200-1350 for an individual or ≥2400-$2700 for a family (values depend on survey year with increases over time). Cox proportional hazards models using age as the time scale were utilized to determine: 1) association of HDHP status with overall survival (OS) and cancer survival (CS; i.e., freedom from cancer death) among cancer survivors, and 2) how associations differed for survivors compared to those without a cancer history. Models accounted for the NHIS survey design and survey weights and were adjusted for insurance status, marital status, sex, comorbidities, education, income, national region, and cancer site and time since cancer diagnosis (if applicable). Sensitivity analyses adjusting for age at cancer diagnosis were performed using time since diagnosis as the time scale. Results: A total of 147,254 respondents were identified, 5.9% of whom were cancer survivors. 25.6% of survivors and 28.5% of individuals without a cancer history reported being insured by a HDHP at the time of NHIS participation. HDHP status was associated with worse OS (HR: 1.46, 95% CI = 1.19 - 1.79) and CS (HR: 1.34, 95% CI = 1.01 - 1.77) among cancer survivors overall in the adjusted model. HDHP status was additionally associated with worse OS among the following subgroups of cancer survivors: non-Hispanic White (HR: 1.45, 95% CI = 1.16 - 1.82), income &gt; 400% federal poverty level (HR: 1.65, 95% CI = 1.16 - 2.36), college (HR: 1.47, 95% CI = 1.07 – 2.00) or high school (HR: 1.59, 95% CI = 1.19 - 2.12) education, and multiple cancers (HR: 1.58, 95% CI = 1.06 - 2.36), without clear patterns by sex, comorbidities, insurance, and cancer site. Sensitivity analyses provided similar results. In contrast, among adults without a history of cancer at the time of NHIS participation, HDHP status was not significantly associated with OS (HR: 1.08, 0.96 - 1.21; Pinteraction &lt; .01) or CS (HR: 0.90, 95% CI = 0.70 - 1.14; Pinteraction &lt; .01). Conclusions: This nationwide population-based analysis suggests that HDHPs are associated with both worse overall survival and cancer survival among cancer survivors but are not associated with survival in adults without a history of cancer. HDHPs may financially disincentivize cancer survivors from utilizing necessary medical care to optimize survivorship thereby compromising mortality and cure. Policy changes to limit the proliferation of these plans may improve cancer outcomes.

Supplemental Nutrition Assistance Program (SNAP) policy changes and mammography use in the United States.

11033 Background: The Supplemental Nutrition Assistance Program (SNAP) alleviates food insecurity among low-income households, which has been linked to healthcare access. Several states increased SNAP eligibility by implementing policies that eliminate asset tests and/or broaden income eligibility criteria. This study investigates the associations of SNAP policy changes on mammography use within the past year among low-income females eligible for breast cancer screening. Methods: Income-eligible females ages 40-79 years were identified from the 2006-2019 Behavioral Risk Factors Surveillance System. 28 and 22 states adopted SNAP asset test elimination and income increase policies, respectively. Difference-in-differences analyses compared changes in the percentage of mammography within one year from pre- to post-SNAP policy adoption (asset test elimination or income eligibility increase) between states that did and did not adopt policies expanding SNAP eligibility. The samples were limited to females with household income &lt; 130% and &lt;200% federal poverty level for analyses of asset test elimination and income eligibility increase policies, respectively, to correspond to typical eligibility criteria. Results: A total of 171,684 and 294,647 income-eligible females were included for the asset test elimination and income eligibility increase policy analyses, respectively. Overall, 58.4% reported mammography within 1 year. Adoption of asset test elimination policies was associated with a 2.11 percentage point (95% CI = 0.07 to 4.15, P=0.043) increase in mammography, particularly for non-metropolitan residents (4.14 percentage points, 95% CI = 1.07 to 7.21, P=0.008), those with household income &lt;$25,000 (2.82 percentage points, 95% CI = 0.68 to 4.97, P=0.01), and those residing in states in the South (3.08 percentage points, 95% CI = 0.17 to 5.99, P=0.038) or in states that did not expand Medicaid under the Affordable Care Act (3.35 percentage points, 95% CI = 0.36 to 6.34, P=0.028). There was no significant association between state-level policies broadening SNAP income eligibility and mammography use (-1.07 percentage points, 95% CI = -2.64 to 0.49, P=0.18). Conclusions: This nationwide study suggests that policies eliminating the asset test for SNAP eligibility were associated with increased mammography use within one year, with the most pronounced positive impact observed in Southern states, non-expansion states, non-metropolitan areas, and households with the lowest incomes. Findings highlight the role that states policies have to both meet essential needs and promote health among vulnerable populations.

Predicting therapeutic clinical trial enrollment for underrepresented patients in neuro-oncology using supervised machine learning.

1614 Background: Despite the unique ability of machine learning (ML) techniques to uncover complex interactive effects in datasets, studies exploring predictors of clinical trial enrollment have largely used standard statistical methods to discern associations. Furthermore, there have been limited applications of ML to close existing disparities in clinical trial enrollment of underrepresented patients in neuro-oncology. This study aims to use supervised machine learning to define and validate primary contributors of therapeutic clinical trial enrollment for a) all patients, b) women and c) NIH-designated minority patients with low- and high-grade glioma. Methods: Adult glioma patients who received care from the UCSF Brain Tumor Center between 1997- 2017 were identified in a prospective registry. Bootstrap forest (BF) and Recursive Partitioning (RP) models were created by randomly dividing patients in a 70/30 split into development (DEV) and validation (VAL) cohorts among all patients, women, and NIH-designated minority patients, separately. Model performance was assessed using the area under the curve (AUC) in the DEV and VAL cohorts. Results: Among 1042 patients, 350 patients (33.6%) enrolled in a therapeutic clinical trial. There were 445 women (42.7%), of which 144 (32.4%) enrolled, and 141 minority patients (13.5%), of which 39 (27.7%) enrolled. For all patients, in order of decreasing influence, the BF model selected median neighborhood household income, age, neighborhood poverty level, distance from hospital, tumor location, tumor volume, treatment with chemotherapy, occupation, KPS, insurance status, employment status, seizure at presentation, and volumetric extent of resection (EOR) to predict trial enrollment (DEV AUC: 0.984; VAL AUC: 0.746). For women, the BF model selected distance from hospital, age, household income, neighborhood poverty level, tumor location, treatment with chemotherapy, and KPS for trial prediction (DEV AUC: 0.972; VAL AUC: 0.746), whereas for minority patients, the BF model selected neighborhood poverty level, age, occupation, distance from hospital, tumor volume, insurance status, employment status, and EOR to predict trial enrollment (DEV AUC: 0.9830; VAL AUC: 0.769). The RP model for women designated those with non-White race as less likely to enroll (DEV AUC: 0.735; VAL AUC: 0.665) while the RP model for minority patients characterized those who preferred a non-English language or who were divorced or widowed as less likely to enroll (DEV AUC: 0.775; VAL AUC: 0.601). Conclusions: Supervised machine learning models achieved similar predictive performance among patient subgroups, while uncovering interactions between gender identity, minority status, and sociodemographic variables. These findings can guide targeted recruiting efforts to advance equitable trial enrollment for women and minorities.

Assessing survival effects of persistent poverty and payer status in non-elderly adults with lung or breast cancer.

1608 Background: Persistent poverty (PP), defined as area poverty ≥20% over 30 years has been associated with increased cancer incidence and worse survival. We examined 1) whether residing in a PP area has larger survival effects than areas with similar contemporary poverty rates; 2) whether adjusting for sociodemographics and payer status reduces PP effects; and 3) whether effects differ for relatively poor (lung and bronchus, LCa) vs good prognosis (female breast; BrCa) cancers. Methods: We used Surveillance, Epidemiology, and End Results (SEER) data linked to Medicaid and Medicare enrollment records (2007-2013), with census-tract level indicators for PP and current poverty (CP) as of 2010. We selected adults aged 19-64, diagnosed with LCa or BrCa. We created a hierarchical poverty status measure (PP, CP&gt;20%, CP 10-20%, CP &lt;10%). Primary payer at diagnosis (SEER) was edited using Medicaid and Medicare enrollment records. Covariates include patient sociodemographics (including age, race, sex (LCa only), marital status), rurality, and region. We used Cox proportional hazard models to estimate effects of poverty status and payer on survival, starting with a limited Model I (poverty status, rurality, and cancer stage), adding sociodemographics, region, and diagnosis year (Model II), plus primary payer (Model III). Results: Among LCa (BrCa) 8.8% (5.3%) of 70,964 (246,405) patients lived in PP areas, with 19.1% (13.7%) in areas with CP &gt;20%; primary payers included 51.9% (75.0%) private, 28.7% (16.9%) Medicaid, and 3.1% (1.1%) uninsured. For both cancers, adjusted hazard of death increased with increasing poverty levels; PP areas showed the highest risk (table). The magnitude of the poverty gradient was smaller for LCa vs BrCa. Adjusting for sociodemographic measures and primary payer reduced the magnitude of poverty status effects, particularly for BrCa. Conclusions: We observed significant but distinct associations of poverty status, including PP, with survival for non-elderly adults with LCa and BrCa. With better prognosis, BrCa patients have longer exposure to PP, which may increase the impact on outcomes. Person-level characteristics and health insurance are also key factors affecting care access and survival. These results highlight the need to consider both area context and personal socioeconomic characteristics when targeting and evaluating interventions to enhance survival outcomes. [Table: see text]