Socioeconomic Status and Nonadherence to Antihypertensive Drugs: A Systematic Review and Meta-Analysis

Background: Although conventional wisdom suggests that low socioeconomic status (SES) is a robust predictor of medication nonadherence, the strength of this association remains unclear. Objectives: 1) To estimate the proportion of studies that identified SES as a potential risk indicator of nonadherence, 2) to describe the type of SES measurements, and 3) to quantify the association between SES and nonadherence to antihypertensive pharmacotherapy. Methods: A systematic review and meta-analysis research design was used. We searched multiple electronic databases for studies in English or French examining nonadherence to antihypertensive medications measured by electronic prescription databases where explanatory factors were considered. Two authors independently assessed quality, described the SES measure(s), and recorded its association with nonadherence to antihypertensives. A random-effects model meta-analysis was performed, and heterogeneity was examined by using the 12 statistic. Results: Fifty-six studies with 4,780,293 subjects met the inclusion criteria. Twenty-four of these studies (43%) did not report any SES measures. When it was reported (n = 32), only seven (13%) examined more than one component but none performed a multidimensional assessment. Most of the studies relied on income or income-related measures (such as prescription-drug benefits or co-payments) (27 of 32 [84%]). meta-analysis could be quantified in 40 cohorts reported in 30 studies. Overall, the pooled adjusted risk estimate for nonadherence according to SES (high vs low) was 0.89 (95% confidence interval 0.87-0.92; l(2) = 95%; P < 0.001). Similar patterns were observed in all subgroups examined. Conclusions: Published studies have not found a strong association between low SES and nonadherence to antihypertensive medications. However, important limitations in the assessment of SES can be identified in virtually all studies. Future studies are required to ascertain whether a stronger association is observed when SES is determined by comprehensive measures.