Disparities in the use of procedures by race, ethnicity, sex, and socioeconomic status (SES) have been widely documented including invasive cardiovascular interventions 1 2 , joint replacement surgery 2 3 , and other new or expensive technology 4 5 . These disparities may reflect either potential access (e.g. insurance or regular source of care) or realized access (visit number), 6 expenses (often not fully covered by insurance) 7 in addition to slower diffusion of innovation to minority patients or possibly to physicians and hospitals serving them 8 9 10 11 .

In contrast, there is considerably less evidence for disparity in use of drugs for common, chronic conditions 12 . For example, there are few racial and ethnic disparities in inpatient medical management of congestive heart failure 13 and coronary artery disease 14 or in outpatient management of hypertension 15 .

Statins may be an exception. They may be used less frequently among African Americans and poor patients 16 17 18 19 20 21 and these patients may be less likely to achieve target low density lipoprotein cholesterol (LDL-C) goal 22 23 . These findings have been variously limited by absence of cholesterol measurement, suboptimal SES measurement, and/or failure to fully apply the Third Adult Treatment Panel (ATP III) recommendations for treatment of elevated LDL-C.

Using recent US national data that included details on LDC-C levels, statin use, socio-demographic characteristics including race/ethnicity and SES, and healthcare access/utilization, three hypotheses were examined: 1) among persons not receiving statins, race/ethnicity, and lower SES would be associated with statin eligibility; 2) among persons currently receiving statins, race/ethnicity, and lower SES would be associated with lower likelihood of achieving LDL-C goals, and; 3) access/utilization related factors would attenuate these disparities.

Altogether, the NHANES surveys included 18,042 adults age 21-79. Data for FRS scoring was available on 15,260 (91% population weighted) of the sample. Persons with missing FRS information were more likely to be women (57% vs. 51%, p < .01), to have household incomes < 100% poverty level (17% vs. 12%, p < .01), and more likely (p < .01) to be African American (20% vs. 10%) or other race (7% vs. 5%). LDL-C levels were collected on a subset (N = 6913, population weighted = 45%) of those with FRS data; those without LDL-C were more likely to have household incomes < 100% poverty level (13% vs. 10%). Complete socio-demographic and LDL-C data were available on 6,580 persons. Of those with complete data, 537 (7.7%) reported current statin use. The characteristics of persons currently receiving compared to those not receiving statins are shown in Table 1; those not receiving statins were younger, poorer, disproportionately female, Black or Hispanic, lacked a usual source of care, had fewer visits, and were also more likely to have been surveyed in earlier years (p all < .01).

Among the 6,043 participants not taking statins, 10.4% were eligible but not taking statins. Table 1 (last column) shows the factors associated with being eligible; these groups included: being older, male, non-Hispanic, poorer, less educated, uninsured, and having more visits (p all < .01).

Logistic regression analyses revealed the socio-demographic risk factors for being eligible (among those not taking statins) included being older, male, having lower income, and less education (Table 2). Hispanics were less likely to be eligible, an effect that became not significant after adjustment for the access/utilization variables (primarily language). None of the other socio-demographic effects observed were significantly attenuated by adjustment for the access/utilization variables. Among two-way interactions, the gender*age group effect was significant; the gender disparity in eligibility increased with age (Figure 1).

Table 3 shows ATP III goal attainment among statin users and non-users. Among the 537 persons taking statins, 81.3% were at LDL goal. Goal attainment was less likely in men and poorer persons (p all < .01). The logistic regression analyses revealed that goal attainment was associated with being female and having higher income (Table 4); the effects of age, race/ethnicity, and education were not significant. There was no significant effect of the access/utilization variables. No interactions were statistically significant.

The supplementary analyses of statin eligibility among those not taking statins produced results similar to those presented. These models adjusted for patients reporting cholesterol testing (69%), patient knowledge of own cholesterol level (23%), and patient reporting as to whether the physician recommended treatment (8%); and, excluded those with a history of liver disease (3.7%).

Supplementary analyses of goal attainment examined the potential confounding effect of duration and potency of statin therapy. About 25% of respondents had been on statins for < 1 year, but there was no evidence that duration of therapy predicted goal attainment (<1 year, 78% vs. longer, 80%, p = 0.6). Statin potency was not significantly associated with goal attainment (p = 0.2), and did not affect the AMEs of the socio-demographic variables.

Analysis of this US nationally representative sample revealed significant disparities in the use of statins. Adults eligible, but not taking statins, were more likely to be older, male, of lower income, and less educated. The gender effect increased significantly with age. Among patients currently receiving statins, being male and having less income were associated with failure to attain LDL-C goal.

In contrast to previous US studies that used limited income adjustment 16 17 18 19 20 21 , race/ethnicity was not significantly associated with statin eligibility or goal attainment; the study discrepancies suggest the key role of income.

Much of the US disparity literature has focused on race and ethnicity. These results underscore the significance of sex and SES on appropriate use of statins and on LDL-C goal attainment. Following a myocardial infarction men are more likely to receive appropriate interventions including angiography and revascularization 14 . However, men are more likely to be eligible, but not taking statins, and less likely to be at goal if treated. These findings, while contrasting with studies examining gender differences in the use of invasive procedures, are consistent with the notion that women may be more effective users of ambulatory care than men 29 , and with findings that among those with high cholesterol women are both more likely to be aware of their condition 30 and more likely to be treated 21 . In addition, male sex and older age are included in FRS. This effectively lowers treatment thresholds among men and older persons, possibly contributing to sex and/or age disparities.

Among untreated persons, those with less income and less education are more likely to be eligible. These findings are consistent with previous studies showing that low SES is associated with less adequate care 12 31 32 including less statin initiation and persistence among those with lower income 33 34 35 . These effects may reflect barriers related to cost 36 and possibly patient beliefs 37 .

There was little impact of access/utilization-related factors on disparities, other than for Hispanics. This may reflect a dominating effect of statin cost and lack of measures of usual source of primary care. At the time of this study, most statins were expensive and having insurance (including Medicare during this era) did not ensure prescription coverage. Even among those with insurance, higher copayments, and formulary restrictions deter statin use 38 39 . Furthermore, physicians consider formulary restrictions and patient out-of-pocket costs when making prescribing decisions 7 40 . However, it is worth noting that the findings on SES disparities are consistent with studies from countries with more equitable health systems (less socio-economically driven access barriers) including Australia 41 and Denmark 42 . Because these studies did not adjust for FRS, and lower SES is associated with a more adverse FRS profile 43 they likely under-estimate disparities in statin use. Taken together, these studies are consistent with research on the diffusion of new technologies, including statins, showing lower SES persons lag behind in the uptake of those new interventions 44 .

The protective Hispanic effect, i.e. a lower likelihood of Hispanics being eligible, and its attenuation with adjustment for language is consistent with studies demonstrating Hispanics have better adjusted health status than Whites, a benefit that attenuates with greater acculturation 45 46 47 .

Given the powerful effects of statins on cardiovascular and all-cause mortality, these results are concerning. Less optimal management of cholesterol among men and lower SES persons may contribute to higher CHD mortality 48 . The under-treatment of lower SES patients may exacerbate their risk for higher CHD mortality and contribute to widening disparities in CHD mortality 48 . In addition, because FRS does not fully account for the higher CHD risk in lower SES persons, fewer lower SES persons are identified for treatment than warranted 48 . Thus, lower SES persons may be at triple jeopardy: under-identified for treatment, undertreated once identified as eligible, and less likely to achieve treatment goals.

There are several potential explanations for the overall findings. Differences in statin eligibility among untreated patients could reflect physician and/or patient factors. However, an analysis adjusting for whether or not persons reported their physician recommended treatment produced similar results. The absence of an apparent effect of physician recommendation suggests that patient factors including acceptance of prescriptions for statins or differences in adherence barriers such as cost may contribute to higher rates of statin eligibility among the untreated. The overall low rate of physician recommendation among untreated patients (probably related in part to sequencing conditional questions), and potential bias in respondent recall of physician recommendations suggests caution in inferring an absence of physician contribution to these disparities. Further study is needed to determine the relative roles of patient factors (e.g. cost or beliefs) or physician factors (failure to adhere to guidelines) in contributing to these disparities. Doing so will facilitate the design of interventions to mitigate these disparities.

In conclusion, these US national data show that, among persons not taking statins, those with less income and men are more likely than their respective counterparts to be eligible, and, among those taking statins, these groups are also less likely to attain their LDL-C goal. Further study is needed to identify specific amenable patient and/or physician factors that contribute to these disparities.

The authors declare that they have no competing interests.

PF designed study, conducted analyses, interpretation of data and led writing. DT contributed to statistical analyses, interpretation of data and writing. PW contributed data preparation, interpretation of data and writing. KF obtained funding and contributed to writing. All authors read and approved the final manuscript.