<![CDATA[The Social Side of Health]]>The Social Side of Health explores how social and structural factors shape health outcomes. Hosted by Lauren Carson, the podcast bridges social science and public health to examine how context, inequality, and lived experience influence access to care and health equity.

]]>https://riverside.comRiverside.fm (https://riverside.com)Sat, 18 Jul 2026 01:42:00 GMTSat, 02 May 2026 22:07:51 GMT60Lauren Carson<p><i>The Social Side of Health</i> explores how social and structural factors shape health outcomes. Hosted by Lauren Carson, the podcast bridges social science and public health to examine how context, inequality, and lived experience influence access to care and health equity.</p>episodicLauren Carsonlaurencarson293@gmail.comno<![CDATA[Beyond Coverage: Why Insurance isn't Enough for Preventive Care]]>What does it actually mean to have access to healthcare? In this episode of The Social Side of Health, we take a closer look at a question that seems simple but is not. If a woman has health insurance, does that mean she can access preventive care? Drawing on an analysis of 131,144 women from the CDC’s Behavioral Risk Factor Surveillance System (BRFSS), this episode examines cervical cancer screening through an intersectional lens. Using logistic regression, we look at how insurance status and income work together to shape whether women are up to date on pap smears.

The findings challenge a common assumption in public health. Insurance status alone was not a statistically significant predictor of screening (p = 0.171), and low income alone was also not significant (p = 0.151). However, their interaction was statistically significant (OR = 0.586, p = 0.008), meaning insured women with low income had about 41% lower odds of being up to date on screening compared to insured women who were not low income. Model fit also improved significantly when this interaction was added (Δχ² = 7.555, p = 0.006). In other words, insurance may be necessary, but it is not sufficient. Structural barriers like time, transportation, and cost still shape whether care is actually accessible. Grounded in Kimberlé Crenshaw’s framework of intersectionality, this episode connects quantitative findings with lived experience to show how overlapping social positions shape health outcomes.

Key Stats N = 131,144. 97.3% up to date on screening. Interaction OR = 0.586 (95% CI: 0.395 to 0.868), p = 0.008. Nagelkerke R² = 0.027.

Sources (Selected): Crenshaw (1989, 1991); Bauer (2014); Hankivsky (2012); Viruell-Fuentes et al. (2012); USPSTF (2018); Fontham et al. (2020); Sommers et al. (2017); Garfield et al. (2019); CDC BRFSS (2023).

Notes: This episode was developed as part of a graduate-level public health project. Analysis was conducted in SPSS. Full model output, cleaned dataset, and complete citations are available upon request.

]]>d362fb88-75f1-43a1-bdd4-bc4271741126Mon, 04 May 2026 17:28:08 GMT<p>What does it actually mean to have access to healthcare? In this episode of <i>The Social Side of Health</i>, we take a closer look at a question that seems simple but is not. If a woman has health insurance, does that mean she can access preventive care? Drawing on an analysis of 131,144 women from the CDC’s Behavioral Risk Factor Surveillance System (BRFSS), this episode examines cervical cancer screening through an intersectional lens. Using logistic regression, we look at how insurance status and income work together to shape whether women are up to date on pap smears.</p><p>The findings challenge a common assumption in public health. Insurance status alone was not a statistically significant predictor of screening (p = 0.171), and low income alone was also not significant (p = 0.151). However, their interaction was statistically significant (OR = 0.586, p = 0.008), meaning insured women with low income had about 41% lower odds of being up to date on screening compared to insured women who were not low income. Model fit also improved significantly when this interaction was added (Δχ² = 7.555, p = 0.006). In other words, insurance may be necessary, but it is not sufficient. Structural barriers like time, transportation, and cost still shape whether care is actually accessible. Grounded in Kimberlé Crenshaw’s framework of intersectionality, this episode connects quantitative findings with lived experience to show how overlapping social positions shape health outcomes.</p><p></p><p><b>Key Stats</b> N = 131,144. 97.3% up to date on screening. Interaction OR = 0.586 (95% CI: 0.395 to 0.868), p = 0.008. Nagelkerke R² = 0.027.</p><p></p><p><b>Sources (Selected)</b>: Crenshaw (1989, 1991); Bauer (2014); Hankivsky (2012); Viruell-Fuentes et al. (2012); USPSTF (2018); Fontham et al. (2020); Sommers et al. (2017); Garfield et al. (2019); CDC BRFSS (2023).</p><p></p><p><b>Notes</b>: This episode was developed as part of a graduate-level public health project. Analysis was conducted in SPSS. Full model output, cleaned dataset, and complete citations are available upon request.</p>no00:01:34Beyond Coverage: Why Insurance isn't Enough for Preventive Carefull