Discussion

Our research reveals a prevailing pattern where patients with adverse social determinants of health, such as low-income, limited education, and insufficient access to healthcare resources, are significantly more prone to CRMN. Young respondents, unmarried individuals, females, those with less education, and participants in the South had a higher proportion of CRMN compared to older, married individuals, males, and those with higher education, residing in other regions. The comparison between individuals with and without CVD risk factors provided critical insight into how CRMN varies by clinical conditions and risk factors. The observed differences highlight the need for condition-specific strategies while also framing CRMN as a broader systemic issue. These findings emphasize the importance of addressing CRMN through both population-wide interventions and targeted efforts for clinically vulnerable groups. Additionally, they highlight the significant role of financial and social barriers in shaping access to medication and adherence, with substantial implications for overall health outcomes.

Our results suggest that non-adherence was lowest in participants over 65 years of age among all three risk factor groups (3.4% in participants with no CVD risk factors, 3.6% in those with one CVD risk factor, and 4.4% among individuals with more than one CVD risk factor). (Figure 1) This could be explained by the rise in the number of comorbid diseases in older individuals, increasing health awareness with age, greater resource allocation towards medications, and better prescription drug benefits like the Medicare Part D programme (Zhang et al., Reference Zhang, Bhaumik and Meltzer2022: 2004–2014; ‘NHIS - About the National Health Interview Survey’, 2023).

Our analysis also determined that females with more than one CVD risk factor had higher odds of being non-adherent compared to males (OR 1.59, 95% CI, 1.28–1.98). Although previous evidence shows that women are more likely to seek care compared to men, some studies suggest that women as primary caregivers prioritize their family’s health over their own (Rolnick et al., Reference Rolnick, Pawloski, Hedblom, Asche and Bruzek2013; Thompson et al., Reference Thompson, Anisimowicz, Miedema, Hogg, Wodchis and Aubrey-Bassler2016; Höhn et al., Reference Höhn, Gampe, Lindahl-Jacobsen, Christensen and Oksuyzan2020). Additionally, an increasing financial burden based on the number of dependent children could also significantly contribute towards lower medication adherence in females (Rolnick et al., Reference Rolnick, Pawloski, Hedblom, Asche and Bruzek2013; Zhang et al., Reference Zhang, Crowe and Meltzer2017). Additional research reveals that women are more prone to medication side effects, such as statin-induced myopathy, and have higher rates of depressive disorders. Moreover, women often receive substandard care, encounter lower levels of social support, and demonstrate lower awareness of disease risks (Bird et al., Reference Bird, Fremont, Bierman, Wickstrom, Shah, Rector, Horstman and Escarce2007; Nekui et al., Reference Nekui, Galbraith, Briesacher, Zhang, Soumerai, Ross-Degnan, Gurwitz and Madden2021; Venditti et al., Reference Venditti, Bleve, Morano and Filardi2023). This highlights the importance of developing better healthcare policies for younger adults not covered by Medicaid and women to facilitate reducing the disparities that are associated with CRMN (Zhang et al., Reference Zhang, Bhaumik and Meltzer2022).

Among all the risk factor groups, higher proportions of CRMN were found among respondents who received less than a high school level of education followed by those with some form of college education (Lee and Khan, Reference Lee and Khan2016). The former may face significant strain with a higher chance of being unemployed or failing to maintain a steady income (‘Trends in High School Dropout and Completion Rates in the United States’, 2024). Either situation can cause financial strain and affect their insurance status as adults under 65 are primarily dependent on their employer-based insurance thereby impacting their medication adherence (Oates et al., Reference Oates, Juarez, Hansen, Kiefe and Shikany2020; Nekui et al., Reference Nekui, Galbraith, Briesacher, Zhang, Soumerai, Ross-Degnan, Gurwitz and Madden2021; ‘Trends in High School Dropout and Completion Rates in the United States’, 2024). In a cross-sectional analysis of the NHIS data between 2010–2015, Su, Chia-Ping et al. determined that people with non-standard jobs like freelance work, temporary contract-based employment, and working in small establishments were more likely to be uninsured (Su et al., Reference Su, Asfaw, Tamers and Luckhaupt2019). Our findings suggest that a robust social safety net that includes drug benefits might help mitigate the risk of CRMN among low-income and lowereducation groups.

Studies have found that poor economic status and underlying disease were negatively associated with self-rated health (Basirimoghadam et al., Reference Basirimoghadam, Rafii and Ebadi2020; Cialani and Mortazavi, Reference Cialani and Mortazavi2020). The inability to access health resources due to financial hardship aggravates psychological distress and causes deterioration of overall well-being, making it more challenging to afford medications (Tucker-Seeley et al., Reference Tucker-Seeley, Harley, Stoddard and Sorensen2013). This may explain our findings that respondents from high-income households were more likely to be adherent compared to lower-income families irrespective of their disease status or the risk factor groups. Our study also determined that, within all risk factor groups, participants with three or more children had significantly higher non-adherence rates than those with no children. Studies found that families with children and in particular, low-income families are unable to bear the burden of insurance and out-of-pocket healthcare costs, which prove detrimental to their health needs (Wisk and Witt, Reference Wisk and Witt2012; Dong et al., Reference Dong, Tsang, Kotian, Zeng, Tran and Wang2021).

In our assessment, although ethnicity was not a notable contributing factor toward medication adherence, there were significant regional differences observed across the country. Individuals from the South with more than one CVD risk factor were 1.59 times more likely than those from the Northeast to experience CRMN. It is prudent to note that some of the states in the Southern region of the U.S. are among the few that have chosen not to expand their Medicaid. According to the Centres for Disease Control, the residents of the Medicaid non-expansion states were more likely to be uninsured as they are neither eligible for Medicaid nor for other subsidized insurance coverage plans if their income is in the low to moderate range which would potentially affect medication adherence among these populations (Heller et al., Reference Heller, Joshi, Sircar and Hayatghaibi2023; Terlizzi and Cohen, Reference Terlizzi and Cohen2022).

Besides insurance, the regional variation in adherence can also be affected by factors like polypharmacy and complex drug regimens involving taking multiple pills at different times of the day, poor access to pharmacies especially in rural areas, and higher out-of-pocket expenses in areas with predominantly low-income populations (Yang, Reference Yang2020). These can be rectified by introducing better prescription practise guidelines involving generic fixed-dose drug combinations which will reduce the costs as well as the number of pills, increasing doorstep delivery of medications by switching to mail-order or online pharmacy practises (Jimmy and Jose, Reference Jimmy and Jose2011; Marcum et al., Reference Marcum, Driessen, Thorpe, Gellad and Donohue2014).

Our results also revealed that CRMN was higher among current smokers compared to non-smokers. This may be directly linked to the greater expenditure of their annual income on tobacco in comparison to medication (Lal et al., Reference Lal, Mohebi, White, Scollo and McCaffrey2022). Additionally, in those classified as obese with a BMI of greater than 30, CRMN was significantly higher than in those with lower BMIs. Previous studies propose that weight-based bias perpetuated by the community has possibly led to less desire and motivation to seek care by overweight or obese people. Similarly, physician perceptions that obese patients are less likely to be adherent can further reinforce the bias by influencing the management and treatment of these. Interestingly, an individual’s annual medical care costs increase significantly with an increase in the class of obesity, going from 68.4% in class 1 to 233.6% in class 3 which can be due to a greater number of comorbidities in obese patients (Cawley et al., Reference Cawley, Biener, Meyerhoefer, Ding, Zvenyach, Smolarz and Ramasamy2021).

Medications for cardiovascular diseases and their risk factors represent a significant portion of annual spending. Recent years have seen the approval of costly, patented drugs like angiotensin receptor-neprilysin inhibitors (ARNIs) and PCSK9 inhibitors. The Inflation Reduction Act of 2022 aims to address this by capping insulin costs at $35/month, providing free adult vaccines, limiting out-of-pocket expenses to $2000 annually, allowing Medicare to negotiate drug prices, and requiring rebates from drug companies for rapid price increases (Birger et al., Reference Birger, Kaldjian, Roth, Moran, Dieleman and Bellows2021; ‘Inflation Reduction Act and Medicare | CMS’, n.d.; Varghese et al., Reference Varghese, Liu and Kazi2021). While this landmark law represents a significant step, ongoing research is required to evaluate the impact and effectiveness on drug affordability and accessibility, especially due to the limited Medicare expansion in a few southern states. With rising healthcare costs directly attributed to the struggle to afford medication, it is also imperative to strategize and promote healthy habits (Shrank et al., Reference Shrank, DeParle, Gottlieb, Jain, Orszag, Powers and Wilensky2021). Lee et al. demonstrated that lifestyle modifications including cessation of smoking and a weight-loss diet were statistically associated with medication adherence, indicating the importance of interventions such as motivational education programmes (Lee et al., Reference Lee, Kim, Lee, Kim, Shin, Park, Ahn, Kim, Lee, Kim, Lee, Lee, Lee, Kim and Park2018). These features are potential modifying factors that are attributable to CRMN.

These results have important implications for health policy. Expanding Medicaid in non-expansion states, streamlining prior authorization procedures, and incorporating risk-based flags into electronic health records may help identify individuals at risk for CRMN (Cover Story | Affordability, 2018; Jew et al., Reference Jew, Okawa, Barbieri, McCaffrey, Hayward and Werth2020). Policies that cap prescription drug prices, enable bulk purchasing, and incentivize generic alternatives could alleviate cost burdens (‘340B Drug Pricing Program | HRSA’, n.d.; Clark and Puthiyath, Reference Clark and Puthiyath2022; Gaffney et al., Reference Gaffney, Bor, Himmelstein, Woolhandler and McCormick2020). Furthermore, promoting community-based outreach, motivational education programmes, and lifestyle medicine interventions may enhance adherence, particularly among those facing economic and social barriers. As health systems and policymakers work toward improving population health, addressing CRMN must remain a central priority.