Dataset Information

Disparities in all-cause mortality with potentially inappropriate medication use: Analysis of the Reasons for Geographic and Racial Differences in Stroke study.

ABSTRACT:

Objectives

Health disparities across different socioeconomic subgroups have been reported in previous studies. Mortality with potentially inappropriate medication (PIM) use may be subject to similar disparities. We aimed to assess the association between PIM use and all-cause mortality and the effect of disparity parameters (sex, race, income, education, and location of residence) on this relationship.

Methods

This longitudinal cohort study included 26,399 U.S. adults aged 45 years and older from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, of which 13,475 participants were aged 65 years and older (recruited 2003-2007). PIM use and drug-drug interactions (DDIs) were identified through the 2015 Beers Criteria and a clinically significant DDIs list by the American Family Physicians, respectively. Cox regression was used to assess disparities in mortality with PIM use, iteratively adjusting for disparity parameters and other covariates. The full models included interaction terms between PIM use and other covariates. A similar method was used for the analyses of disparities in mortality with DDIs.

Results

Approximately 87% of older adults used at least 1 drug listed in the Beers Criteria, and 3.8% of all participants used 2 or more drugs with DDIs. In the adjusted analysis, an increased risk of mortality was observed among whites with PIM use (hazard ratio [HR] = 1.27 [95% CI 1.10-1.47]). The higher mortality rate was observed among blacks without PIM use (1.34 [1.09-1.65]). Lower income and education were independent predictors for higher mortality.

Conclusion

Racial differences in all-cause mortality with PIM use were observed. Further research is needed to better understand the contributing factors of such disparities to develop appropriate interventions.

SUBMITTER: Rahman MM

PROVIDER: S-EPMC7796934 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPrior work has identified disparities in the quality and outcomes of healthcare across socioeconomic subgroups. Medication use may be subject to similar disparities.ObjectiveTo assess the association between demographic and socioeconomic factors (gender, age, race, income, education, and rural or urban residence) and appropriateness of medication use.MethodsUS adults aged ≥45 years (n = 26,798) from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study were included in the analyses, of which 13,623 participants aged ≥65 years (recruited 2003-2007). Potentially inappropriate medication (PIM) use in older adults and drug-drug interactions (DDIs) were identified through 2015 Beers Criteria and clinically significant drug interactions list by Ament et al., respectively as measures of medication appropriateness. Multivariable logistic regression was used to assess the association of disparity parameters with PIM use and DDIs. Interactions between race and other disparity variables were investigated.ResultsApproximately 87% of the participants aged ≥65 years used at least one drug listed in the Beers Criteria, and 3.8% of all participants used two or more drugs with DDIs. Significant gender-race interaction across prescription-only drug users revealed that white females compared with white males (OR = 1.33, 95% CI 1.20-1.48) and black males compared with white males (OR = 1.60, 95% CI 1.41-1.82) were more likely to receive PIM. Individuals with lower income and education also were more likely to use PIM in this sub-group. Females were less likely than males (female vs. male: OR = 0.55, 95% CI 0.48-0.63) and individuals resided in small rural areas as opposed to urban areas (small rural vs. urban: OR = 1.37, 95% CI 1.07-1.76) were more likely to have DDIs.ConclusionDemographic and socioeconomic disparities in PIM use and DDIs exist. Future studies should seek to better understand factors contributing to the disparities in order to guide development of interventions.