Social Determinants of Cost-Related Medication Nonadherence in the All of Us Cohort

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Abstract

Background This study aimed to examine the social determinants of health (SDH) associated with Cost-related medication nonadherence (CRMNA). Methods A cross-sectional analysis was conducted using data from the All of Us Research Program to identify SDH features associated with CRMNA. CRMNA include inability to afford prescription medication, skipped doses, reduced dosage, selection of lower-cost alternatives, use of alternative therapies, purchasing medications from another country, and delayed prescription filling. A network analysis using the Fruchterman-Reingold algorithm was performed to visualize correlations among SDH features and CRMNA. SDH variables most strongly correlated with CRMNA were analyzed using binary logistic regression to estimate their association with each CRMNA, adjusting for demographic variables. Results According to the network analysis, the SDH features most frequently associated with CRMNAs include housing problems, worries about food insecurity, and experiencing poor attention by healthcare professionals. In the adjusted binary logistic regression model, Individuals who reported concerns about food not lasting were more than twice as likely to report overall CRMNA (adjusted odds ratio [AOR] = 2.29; 95% CI: 2.19–2.40; p < 0.05). Other significant SDH predictors of CRMNA included feeling unheard by a doctor (AOR = 1.59; 95% CI: 1.50–1.69; p < 0.05), experiencing housing problems (AOR = 1.40; 95% CI: 1.36–1.46; p < 0.05), and reporting perceived discrimination (AOR = 1.36; 95% CI: 1.32–1.40; p < 0.05). Conclusion This study highlights the multifaceted impact of SDH on CRMNA, emphasizing the critical roles of food insecurity, housing problem, and negative healthcare experiences in shaping medication adherence behaviors.
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Abstract

Background This study aimed to examine the social determinants of health (SDH) associated with Cost-related medication nonadherence (CRMNA).

Methods

A cross-sectional analysis was conducted using data from the All of Us Research Program to identify SDH features associated with CRMNA. CRMNA include inability to afford prescription medication, skipped doses, reduced dosage, selection of lower-cost alternatives, use of alternative therapies, purchasing medications from another country, and delayed prescription filling. A network analysis using the Fruchterman-Reingold algorithm was performed to visualize correlations among SDH features and CRMNA. SDH variables most strongly correlated with CRMNA were analyzed using binary logistic regression to estimate their association with each CRMNA, adjusting for demographic variables.

Results

According to the network analysis, the SDH features most frequently associated with CRMNAs include housing problems, worries about food insecurity, and experiencing poor attention by healthcare professionals. In the adjusted binary logistic regression model, Individuals who reported concerns about food not lasting were more than twice as likely to report overall CRMNA (adjusted odds ratio [AOR] = 2.29; 95% CI: 2.19–2.40; p < 0.05). Other significant SDH predictors of CRMNA included feeling unheard by a doctor (AOR = 1.59; 95% CI: 1.50–1.69; p < 0.05), experiencing housing problems (AOR = 1.40; 95% CI: 1.36–1.46; p < 0.05), and reporting perceived discrimination (AOR = 1.36; 95% CI: 1.32–1.40; p < 0.05).

Conclusion

This study highlights the multifaceted impact of SDH on CRMNA, emphasizing the critical roles of food insecurity, housing problem, and negative healthcare experiences in shaping medication adherence behaviors. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study did not receive any funding Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics statement The All of Us Research Program is approved by the All of Us Institutional Review Board. The current study used only de-identified data accessed through the All of Us Researcher Workbench and was therefore deemed exempt from additional IRB review. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability All data produced in the present study are available upon reasonable request to the authors

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