Abstract A006: Disparities, social determinants of health, and ovarian cancer: predicting ovarian cancer using sociodemographic information and comorbidities as risk factors

Abstract Introduction In this study, we aimed to identify associations between ovarian cancer (OC) and patient information, including demographics and comorbidities in order to increase awareness of OC risk factors and the ways in which disparities affect individual risk. Methods Administrative data analysis was performed using Florida state inpatient data collected by the Healthcare Cost and Utilization Project in 2012. Demographic variables included age, race, insurance type, and income level. Comorbidities included hypothyroidism, diabetes, hysterectomy, obesity, alcohol abuse, and drug abuse. For each variable, descriptive and logistic regression analyses were performed using SAS software and confirmed with SPSS software to determine frequencies within binary OC outcomes and calculate associations. Results Descriptive analysis revealed that OC was most frequent in white women (73.47%) over 65 (50.17%), who were Medicare beneficiaries (57.00%) within the second quartile of annual income ($38,000-$48,000) (30.71%). Most OC patients did not have any comorbidities. Logistic regression analysis revealed higher risk of OC in women over 65 compared to younger women (OR= 4.277; 95% CI= 3.585-5.103). Black women had reduced odds of OC compared to White women (OR=0.790; 95% CI= 0.693-0.900). Privately insured women had higher odds of OC compared to women with Medicare (OR= 1.426; 95% CI= 1.245-1.634). The risk of OC was reduced in patients in the first, second, and third quartiles of annual income when compared to the highest quartile of annual income (OR= 0.606; 95% CI= 0.527-0.698, OR= 0.618; 95% CI= 0.537-0.710, OR= 0.644; 95% CI= 0.557-0.743, respectively). The risk of OC was increased in women with hypothyroidism (OR= 1.083; 95% CI= 1.021-1.148), diabetes (OR= 1.134; 95% CI= 0.973-1.331), and women who had a hysterectomy (OR= 18.543; 95% CI= 15.262-22.530), compared to those without. Odds of OC were significantly reduced in women with obesity (OR= 0.574; 95% CI= 0.503-0.654) compared to those without. Women who abused alcohol or drugs had lower odds of OC than those who did not (OR= 0.296; 95% CI= 0.205-0.426, OR= 0.280; 95% CI= 0.205-0.382, respectively). Conclusions This study identifies OC risk factors and highlights differences in the prevalence and risk of OC between women of different sociodemographic groups and between women with and without various comorbidities. Groups with socioeconomic privilege were at higher risk of OC. Financial stability and access to healthcare increase the likelihood of receiving a diagnosis, suggesting potential detection bias. Decreased risk of OC was observed in patients with stigmatized comorbidities such as obesity and substance abuse disorders. Under-investigation of symptoms is common in patients with these conditions, leading to underdiagnosis. Health and socioeconomics are inextricable, so it is necessary to understand the relationship between these aspects of patient health and OC to more accurately assess individual risk. Citation Format: Anna E. Langston, Zahra Bahrani-Mostafavi. Disparities, social determinants of health, and ovarian cancer: predicting ovarian cancer using sociodemographic information and comorbidities as risk factors [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A006.

Authors

Institutions

Publication Details

Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2024-09-21
DOI
https://doi.org/10.1158/1538-7755.disp24-a006
Primary Topic
Cancer Risks and Factors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract A006: Disparities, social determinants of health, and ovarian cancer: predicting ovarian cancer using sociodemographic information and comorbidities as risk factors

Zahra Bahrani-Mostafavi, Anna E. Langston
Cancer Epidemiology Biomarkers & Prevention
Cancer Risks and Factors
article

Abstract A006: Disparities, social determinants of health, and ovarian cancer: predicting ovarian cancer using sociodemographic information and comorbidities as risk factors

Zahra Bahrani-Mostafavi, Anna E. Langston
article en

Abstract

Abstract Introduction In this study, we aimed to identify associations between ovarian cancer (OC) and patient information, including demographics and comorbidities in order to increase awareness of OC risk factors and the ways in which disparities affect individual risk. Methods Administrative data analysis was performed using Florida state inpatient data collected by the Healthcare Cost and Utilization Project in 2012. Demographic variables included age, race, insurance type, and income level. Comorbidities included hypothyroidism, diabetes, hysterectomy, obesity, alcohol abuse, and drug abuse. For each variable, descriptive and logistic regression analyses were performed using SAS software and confirmed with SPSS software to determine frequencies within binary OC outcomes and calculate associations. Results Descriptive analysis revealed that OC was most frequent in white women (73.47%) over 65 (50.17%), who were Medicare beneficiaries (57.00%) within the second quartile of annual income ($38,000-$48,000) (30.71%). Most OC patients did not have any comorbidities. Logistic regression analysis revealed higher risk of OC in women over 65 compared to younger women (OR= 4.277; 95% CI= 3.585-5.103). Black women had reduced odds of OC compared to White women (OR=0.790; 95% CI= 0.693-0.900). Privately insured women had higher odds of OC compared to women with Medicare (OR= 1.426; 95% CI= 1.245-1.634). The risk of OC was reduced in patients in the first, second, and third quartiles of annual income when compared to the highest quartile of annual income (OR= 0.606; 95% CI= 0.527-0.698, OR= 0.618; 95% CI= 0.537-0.710, OR= 0.644; 95% CI= 0.557-0.743, respectively). The risk of OC was increased in women with hypothyroidism (OR= 1.083; 95% CI= 1.021-1.148), diabetes (OR= 1.134; 95% CI= 0.973-1.331), and women who had a hysterectomy (OR= 18.543; 95% CI= 15.262-22.530), compared to those without. Odds of OC were significantly reduced in women with obesity (OR= 0.574; 95% CI= 0.503-0.654) compared to those without. Women who abused alcohol or drugs had lower odds of OC than those who did not (OR= 0.296; 95% CI= 0.205-0.426, OR= 0.280; 95% CI= 0.205-0.382, respectively). Conclusions This study identifies OC risk factors and highlights differences in the prevalence and risk of OC between women of different sociodemographic groups and between women with and without various comorbidities. Groups with socioeconomic privilege were at higher risk of OC. Financial stability and access to healthcare increase the likelihood of receiving a diagnosis, suggesting potential detection bias. Decreased risk of OC was observed in patients with stigmatized comorbidities such as obesity and substance abuse disorders. Under-investigation of symptoms is common in patients with these conditions, leading to underdiagnosis. Health and socioeconomics are inextricable, so it is necessary to understand the relationship between these aspects of patient health and OC to more accurately assess individual risk. Citation Format: Anna E. Langston, Zahra Bahrani-Mostafavi. Disparities, social determinants of health, and ovarian cancer: predicting ovarian cancer using sociodemographic information and comorbidities as risk factors [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A006.

Cancer Epidemiology Biomarkers & PreventionVol. 33(9_Supplement)
Queens University of Charlotte (US), Atrium Medical Cente (US)
No poverty, Good health and well-being
Openalex Percentile: Top 73%
Cancer Risks and Factors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.