Barriers in utilizing lipid-lowering agents in non-institutionalized population in the U.S.: Application of a theoretical framework.

Cardiovascular diseases are a major cause of death globally. Epidemiological evidence has linked elevated levels of blood cholesterol with the risk of coronary heart disease. However, lipid-lowering agents, despite their importance for primary prevention, are significantly underused in the United States. The objective of this study was to explore associations among socioeconomic factors and the use of antihyperlipidemic agents in 2018 in U.S. patients with hyperlipidemia by applying a theoretical framework. Data from the 2018 Medical Expenditure Panel Survey were used to identify the population of non-institutionalized U.S. civilians diagnosed with hyperlipidemia. This cross sectional study applied the Andersen Behavioral Model to identify patients' predisposing, enabling, and need factors. Approximately 43 million non-institutionalized adults were diagnosed with hyperlipidemia. With the exception of gender and race, predisposing factors indicated significant differences between patients who used antihyperlipidemic agents and those who did not. The relation between income level and use of antihyperlipidemic agents was significant: X2 (4, N = 3,781) = 7.09, p <.001. Hispanic patients were found to be less likely to receive treatment (OR: 0.62; 95% CI: 0.43-0.88), as observed using a logistic model, with controls for predisposing, enabling, and need factors. Patients without health insurance were less likely to use lipid-lowering agents (OR: 0.33; 95% CI: 0.14-0.77). The present study offers essential data for prioritizing interventions by health policy makers by identifying barriers in utilizing hyperlipidemia therapy. Non-adherence to treatment may lead to severe consequences and increase the frequency of fatal cardiac events in the near future.

Introduction

Cardiovascular diseases (CVD) are the major reason of death globally [1]. Based on World Health Organization (WHO) reports, stroke and coronary heart disease (CHD) account for the most global CVD deaths [2]. In the United States, the Centers for Disease Control and Prevention (CDC) has stated that heart disease is the leading cause of death. Heart diseases account for about 1 in every 4 deaths in the U.S, claiming 610,000 lives, with over half of these deaths due to CHD [3]. The expenses associated with heart diseases are enormous, exceeding 200 billion annually [3]. The total costs of CHD by itself amount to about $108.9 billion each year [3].

Epidemiological and clinical literature, including that obtained from the National Cholesterol Education Program (NCEP), has established the relationship between elevated levels of blood cholesterol and the risk of conditions, such as CHD and strokes [4, 5]. Patients with high blood cholesterol were more likely to develop heart disease [3]. It has been documented that for every reduction in cholesterol level, a reduction in the chance of CHD occurrence was observed [6]. The same pattern was observed in short-term clinical trials wherein for every 10% reduction in LDL, led to a similar percentage of reduced risk of CHD [4, 7].

National guidelines suggest lipid modification or the utilizing lipid-lowering agents for primary and secondary prevention of CHD and stroke. Guidelines on blood cholesterol management focused on β-Hydroxy β-methylglutaryl-CoA reductase inhibitor therapy as the primary choice for treatment [8, 9]. Besides statins, the addition of ezetimibe or a proprotein convertase subtilisin/kexin type (PCSK9) inhibitor was recommended for particular cases [9].

Despite the recommendations of all hyperlipidemia guidelines, only half of adults with hyperlipidemia received treatment [10]. This explains why only one-third of patients with high blood cholesterol had the condition under control [10]. To add fuel to the fire, about 29% and over 37% of adults with established CVD and diabetes, respectively, had not utilized any lipid-lowering medication [11].

According to the CDC, the utilization of lipid-lowering agents had varied due to different socioeconomic variables, for instance insurance coverage, race, age, and ethnicity [10, 12]. The results might signal that patients with high blood cholesterol faced barriers when trying to access lipid-lowering agents. Access to lipid-lowering agents is an important factor that explains the serious underutilization of such medications.

The Andersen behavior model was developed in the late 1960s to understand how and why families use health services. The model aimed to assist policy makers in promoting equitable access to healthcare. The model was previously utilized to explain access to different treatments [13-15]. The model suggests that patient’s utilization of healthcare resources is determined by their predisposition to utilize services, factors that impede or enable their utilization, or their need for services. A limited number of studies have explored access to lipid-lowering medications for patients with high blood cholesterol in the U.S. without a theoretical framework.

The goal of this study was to explore the association between socioeconomic factors and the use of antihyperlipidemic agents in patients with hyperlipidemia in the U.S. in 2018 by applying the Andersen behavior model. This is an important goal for public health as the evidence shows how lipid lowering agent lowers CVDs [10, 11].

Materials and methods

Study data

The data are from the 2018 Medical Expenditure Panel Survey (MEPS). The MEPS is a nationally representative survey of the U.S. civilian non-institutionalized population, available since 1996. The MEPS data is publicly available and sponsored by the Agency for Healthcare Research and Quality.

Study design

This is a population-based secondary data study, which used a cross-sectional design for the U.S. civilian non-institutionalized patients with hyperlipidemia to compare patients on therapy regimens comprising lipid-lowering medications to those on regimens without lipid-lowering medications in 2018. The model was developed after considering the literature. The model included population characteristics, including predisposing, enabling, and need factors, all factors that could impact patients’ health behavior or their compliance for the use of lipid-lowering medications. The present study provided an unbiased overview of all groups of therapy used for hyperlipidemia.

Study variables

Patients diagnosed with high blood cholesterol from the 2018 Medical Condition File formed the study population. These patients were obtained from the Agency for Healthcare Research and Quality’s Clinical Classification Software Refined codes. The dependent variable (Hyperlipidemia therapy) was defined as a dichotomous variable: use of lipid-lowering agents versus no hyperlipidemia treatment, from the 2018 Prescribed Medicine File. The independent variables consisted of socioeconomic factors defined by the Andersen behavioral model of healthcare services [16, 17]. The variables include predisposing (gender, age, marital status, race, ethnicity, and education level), enabling (insurance coverage, income level, metropolitan area, and region), and need variables (self-perceived physical & mental health status, smoking, body mass index, hypertension, diabetes millets, stroke, and angina).

Data analysis

A series of descriptive analyses using chi-square testing was conducted to assess differences in the sociodemographic factors of patients between lipid-lowering agents’ users versus non-users. A multivariable logistic regression was calculated to assess the significant socioeconomic variables related with the utilization of treatment. Three logistic models were generated; the predisposing factors were compiled in the first model, the second model included enabling factors, and the third model added the need factors:

Model 1: logitP1 (X) = α +

Model 2: logitP2 (X) = α +

Model 3: logitP3 (X) = α +

The study investigated adults diagnosed with high blood cholesterol from the U.S. adult civilian non-institutionalized population, a subgroup within the MEPS population. Estimates from the population of interest only yielded incorrect standard errors, usually overestimated standard errors, because of the multistage sample design MEPS follows [18]. The sample design was maintained by using the domain analysis, a subpopulation analysis. Domain analysis computes statistics for subgroups, but it accounts for the MEPS population when estimating variance for a subgroup. SAS 9.4 allows for the use of the subpopulation analyses required by a MEPS population.

Results

Over 43 million noninstitutionalized adults (20 years of age and older) were diagnosed with hyperlipidemia in 2018. Among them, 86.90% received treatment (38,040,354) and 13.05% did not receive treatment (5,704,608). Table 1 presents the predisposing characteristics of patients with hyperlipidemia. Fifty-three percent of the weighted study population was 65 years or older, and 40% was between 45–64. A little over half of subjects were male. The majority of patients were white and non-Hispanics. Sixty percent were currently married, and 41.42% had an education level above high school.

Table 1

Population characteristics; predisposing factors.

Predisposing factors	Total number (unweighted)	Patients with hyperlipidemia treatment (unweighted)	Patients without hyperlipidemia treatment (unweighted)	p value
Age				<.001*
20–44	2,680,593 (190)	1,853,030 (131)	827,564 (59)
45–64	17,515,348 (1,423)	15,113,962 (1,218)	2,401,386 (205)
65 and older	23,549,019 (2,168)	21,073,362 (1,941)	2,475,657 (227)
Gender				0.260
Male	23,237,666 (1,891)	20,352,319 (1,660)	2,885,348 (231)
Female	20,507,294 (1,890)	17,688,035 (1,630)	2,819,260 (260)
Race				0.190
White	35,630,231(2,976)	31,176,376 (2,609)	4,453,855 (367)
Black	4,420,464 (513)	3,673,274 (422)	747,191 (91)
Others†	3,694,265 (292)	3,190,704 (259)	503,561 (33)
Ethnicity				<.001*
Hispanic	4,362,631 (480)	3,408,099 (380)	954,532 (100)
Non-Hispanic	39,382,330 (3,301)	34,632,254 (2,910)	4,750,075 (391)
Marital status				0.004*
Married	26,238,620 (2,137)	23,137,335 (1,886)	3,101,285 (251)
Widowed	5,892,207 (561)	5,206,492 (494)	685,715 (67)
Others‡	11,614,134 (1,083)	9,696,527 (910)	1,917,607 (173)
Education level				0.015*
Below High School	4,856,305 (569)	4,079,498 (480)	776,808 (89)
High School	20,769,219 (1,844)	17,857,413 (1,599)	2,911,806 (245)
Above High School	18,119,436 (1,368)	16,103,442 (1,211)	2,015,993 (157)

* significance at 0.05 level

† others includes other race/ multiple race

‡ others includes single or separated

Table 2 describes the enabling factors about the current sample. Ninety-eight percent of the patients with hyperlipidemia were insured, with 62% of them holding a private insurance. Majority of the subjects reported a high-income level. Forty-four of hyperlipidemic patients receiving treatment have excellent and very good self-perceived physical health status compared to 35% of those without treatment (Table 3). The same phenomenon was observed with self-perceived mental health status, patients with treatment reported higher perceived mental status (59%) than patients without treatment (51%). Eighty-five percent patients with diabetes are on a antihyperlipidemic treatment regimen compared with 87.44% of non-diabetic patients.

Table 2

Population characteristics; enabling factors.

Enabling Factors	Total number (unweighted)	Patients with hyperlipidemia treatment (unweighted)	Patients without hyperlipidemia treatment (unweighted)	p value
Insurance coverage				<.001*
Any private	27,079,592 (2,139)	23,929,195 (1,892)	3,150,397 (247)
Public only	16,081,633 (1,584)	13,750,549 (1,358)	2,331,084 (226)
Uninsured	583,735 (58)	360,609 (40)	223,126 (18)
Income level				<.001*
Poor/Negative	4,399,802 (536)	3,648,898 (448)	750,904(88)
Near poor	1,552,884 (158)	1,394,491 (139)	158,394(19)
Low income	5,618,895 (536)	4,661,304 (449)	957,591 (87)
Middle income	11,578,220 (1,042)	9,930,230 (904)	1,647,990 (138)
High income	20,595,159 (1,509)	18,405,430 (1,350)	2,189,729 (159)
Region				0.099
Northeast	7,992,648 (627)	6,726,377 (535)	1,266,270 (92)
Midwest	9,348,481 (827)	8,319,684 (734)	1,028,796 (93)
South	17,651,895 (1,535)	15,343,415 (1,321)	2,308,480 (214)
West	8,751,937 (792)	7,650,877 (700)	1,101,060 (92)

* significance at 0.05 level

Table 3

Population characteristics; need factors.

Need Factors	Total number (unweighted)	Patients with hyperlipidemia treatment (unweighted)	Patients without hyperlipidemia treatment (unweighted)	p value
Physical Health Status				<.001*
Excellent	5,459,491 (375)	4,878,462 (325)	581,030 (50)
Very good	14,258,527 (991(	12,434,837 (848)	1,823,691 (143)
Good	16,671,695 (1,331)	14,440,573 (1,115)	2,231,121 (216)
Fair	7,970,053 (827)	6,362,455 (650)	1,607,598 (177)
Poor	2,750,439 (273)	2,105,671 (207)	644,768 (66)
Mental Health Status				<.001*
Excellent	12,261,144 (895(	10,767,382 (758)	1,493,763 (137)
Very good	14,154,464 (1039)	12,524,093 (900)	1,630,371 (139(
Good	15,325,710 (1,285)	12,796,501 (1,035)	2,529,209 (250)
Fair	4,410,820 (465)	3,392,829 (363(	1,017,991 (102)
Poor	958,067 (113)	741,194 (89)	216,873 (24(
Diabetes
Yes	14,425,574 (1,324)	12,686,041 (1,118)	1,739,534 (206)
No	32,684,631 (2,473)	27,535,958 (2,027)	5,148,673 (446)
High Blood Pressure				0.394
Yes	33,938,952 (2,837)	28,856,386 (2,337)	5,082,566 (500)
No	13,171,253 (960)	11,365,612 (808)	1,805,641 (152(
Angina				0.133
Yes	3,616,854 (281)	3,201,838 (238(	415,016 (43)
No	43,493,351 (3,516)	37,020,160 (2,907)	6,473,191 (609)
Stroke				0.171
Yes	4,887,672 (448(	4,018,182 (366(	869,490 (82(
No	42,222,534 (3,349)	36,203,816 (2,779)	6,018,717 (570)
Smoking Status				0.050
Yes	5,977,949 (508)	4,894,193 (412)	1,083,756 (96)
No	41,132,256 (3,289)	35,327,805 (2,733)	5,804,451 (556)
Body Mass Index				0.028*
Underweight	327,070 (28)	233,341 (20)	93,729 (8(
Normal Weight	10,194,145 (805)	8,451,161 (657)	1,742,984 (148)
Overweight and Obese	36,588,990 (2,964)	31,537,496 (2,468)	5,051,494 (496)

* significance at 0.05 level

Table 4 shows progressively adjusted logistic models of hyperlipidemic patients for receiving treatment. When only predisposing factors were included (model 1), individuals aged 20 to 44 and Hispanics were less prone to receive treatment than those aged 65 or more and non-Hispanics. After enabling factors were added (model 2), patients without insurance and patients living in the Midwest were less prone towards treatment compliance. On addition, the Hispanic population between the ages of 20 to 44 was associated with likelihood of not receiving treatment.

Table 4

Progressively adjusted logistic models of hyperlipidemic agents.

Odds Ratio Estimates	Model 1			Model 2			Model 3
Effect	Point Estimate	95% Wald Confidence Limits		Point Estimate	95% Wald Confidence Limits		Point Estimate	95% Wald Confidence Limits
Age
20–44	0.28*	0.18	0.44	0.27*	0.17	0.42	0.27*	0.170	0.44
45–64 age	0.77	0.59	1.02	0.75	0.56	1.00	0.748	0.55	1.01
65 and older	Reference Group			Reference Group			Reference Group
Gender
Female	0.88	0.70	1.10	0.88	0.70	1.10	0.87	0.69	1.09
Male	Reference Group			Reference Group			Reference Group
Race
Black	0.72	0.51	1.01	0.77	0.54	1.10	0.80	0.56	1.12
Others	0.94	0.56	1.57	1.02	0.63	1.65	1.01	0.63	1.64
White	Reference Group						Reference Group
Ethnicity
Hispanic	0.52*	0.36	0.77	0.60*	0.42	0.86	0.62*	0.43	0.88
Non-Hispanic	Reference Group			Reference Group			Reference Group
Marital status
Widowed	0.97	0.66	1.44	1.08	0.73	1.58	1.09	0.74	1.60
Others	0.82	0.63	1.07	0.91	0.68	1.21	0.90	0.68	1.20
Married	Reference Group			Reference Group			Reference Group
Education level
Below high school	0.82	0.56	1.21	0.97	0.64	1.47	0.99	0.65	1.50
High school	0.80	0.62	1.03	0.86	0.66	1.12	0.88	0.67	1.15
Above high school	Reference Group			Reference Group			Reference Group
Insurance coverage
Public only				0.81	0.60	1.10	0.82	0.60	1.12
Uninsured				0.33*	0.14	0.77	0.33*	0.14	0.77
Any private				Reference Group			Reference Group
Income level
Low income				0.75	0.50	1.12	0.77	0.51	1.16
Middle income				0.81	0.60	1.09	0.83	0.61	1.14
Near poor				1.27	0.64	2.51	1.33	0.66	2.66
Poor/negative				0.80	0.52	1.23	0.81	0.52	1.24
High income				Reference Group			Reference Group
Region
Midwest				1.61*	1.10	2.34	1.59*	1.10	2.30
South				1.35	0.97	1.87	1.33	0.96	1.85
West				1.37	0.99	1.90	1.35	0.96	1.88
Northeast				Reference Group			Reference Group
Physical health status
Fair							0.87	0.50	1.50
Good							0.77	0.47	1.25
Poor							1.05	0.53	2.08
Very good							0.93	0.56	1.55
Excellent							Reference Group
Mental health status
Fair							0.96	0.55	1.67
Good							0.96	0.66	1.38
Poor							0.88	0.43	1.82
Very good							1.08	0.75	1.54
Excellent
Diabetes
No							1.01	0.78	1.31
Yes							Reference Group
Hypertension
No							1.07	0.81	1.40
Yes							Reference Group
Angina
No							1.01	0.70	1.45
Yes							Reference Group
Stroke
No							1.03	0.72	1.48
Yes							Reference Group
Smoking
No							0.90	0.66	1.23
Yes							Reference Group
Body Mass Index
Normal weight							1.05	0.74	1.49
Underweight							1.36	0.71	2.64
Overweight and obese							Reference Group

* statistically significant

The inclusion of need factors did not decrease the association between receiving treatment and patients aged 20 to 44, Hispanics, uninsured, and patients in the Midwest (model 3). However, none of the added need factors were significantly associated with antihyperlipidemic treatment.

Discussion

This study aimed to provide an estimate of the prevalence of hyperlipidemia among noninstitutionalized adults in the U.S. civilian population in 2018, which is an estimated 13.4%. This figure is lower than that reported by the CDC, which estimated that 30% of the U.S. population had hyperlipidemia [19].

This study’s estimation differed from the CDC’s by including patients, wherein their hyperlipidemia report was later validated by a health care professional. In 2012, an estimated 72 million MEPS households self-reported a diagnosis of hyperlipidemia, indicating that the CDC’s figures were drawn from self-reports rather than from reports validated by health care professionals [16]. Although the percentage was less than estimated, this study has already pointed out that more than 47 million U.S. adults have been diagnosed with hyperlipidemia, a main determinant reason for stroke and CHD.

This study has found that an alarming number of patients who had hyperlipidemia (5,704,608) did not use a lipid-lowering agent of any kind, reflecting the general national incidence of hyperlipidemia therapy in 2018. Indeed, this very shortfall instigated the present investigative study, for the Healthy People 2020 initiative aims to increase the prevalence of therapy that uses lipid-lowering agents alongside increasing adherence to such therapy [20].

Concerning the comparison of socioeconomic characteristics of patients who received treatment and patients who did not, this study obtained results similar to those obtained in previous studies. In 2012, for example, the percentage of U.S. adults who underwent hyperlipidemia therapy increased with age [11]. This study has identified a similar trend among patients who have hyperlipidemia, finding that the prevalence of diagnosis and treatment increases with age. This is an expected result considering that the atherosclerotic cardiovascular disease (ASCVD) risk estimator and the Framingham CVD risk calculator, used by clinicians to determine eligibility for hyperlipidemia therapy, treats age as a risk factor [21, 22]. A considerable number of hyperlipidemia patients aged 65 or older had not undergone treatment—2,475,657 altogether. Such a finding comports with the results of investigations made between 2005 and 2012, wherein a considerable number of patients aged 65 or older were found to have not opted for hyperlipidemia therapy despite being eligible for treatment [23].

Most young adults do not meet the criteria for hyperlipidemia therapy as set forth in national guidelines. Further, there is little consensus surrounding the use of lipid-lowering agents for the treatment of young patients. Thus some studies have concluded that early treatment of patients aged 35 to 55 prevents major CHD [24], however, others have recommended that younger adults focus on lifestyle modifications including smoking cessation and stepping up their level of physical activity [25]. Indeed, this study has found that most physicians take such an approach when treating younger adults.

Another important determinant of hyperlipidemia therapy was ethnicity, with Hispanics reporting less use of lipid-lowering agents than non-Hispanics. Some studies reported that Hispanics suffer relatively less mortality and morbidity resulting from CHD and CVD [26, 27], a trend that can potentially explaining underuse. However, reasoning could support the conclusion that Hispanics require less preventive treatment as they are somehow protected from heart disease [26].

One striking finding of comparative analysis has been the finding that comorbid conditions such as diabetes, hypertension, angina, and stroke are of no particular significance. Diabetes was expected to be a significant factor between other comorbid conditions. The 2013 ACC/AHA guidelines identified patients who have diabetes as a group whose members may benefit from statin treatment, a decision that may lead to explain the expectation. This is an alarm finding that patients, particularly with Hispanic origin, have barriers to treatment even with major comorbid conditions diagnoses.

Certainly the other perceived significance of comorbid conditions has varied in the literature. On one hand, McClelland and colleges found hypertension to significantly correlate with the utilization of lipid-lowering medications in members of multiethnic groups who had atherosclerosis [28]. On the other hand, hypertension was found to significantly correlate with the use of or adherence to a regimen of lipid-lowering agents in adults and military veterans who had hyperlipidemia [29-31].

This study had some limitations; the cross-sectional design of MEPS—by its very nature—describes a limited period: the results of this study cannot be generalized to years other than 2018. Moreover, establishing causal relationships from a cross-sectional design presents a special set of difficulties. However, these limitations were not thought so great as to outweigh MEPS data’s ability to supply various clinical and socioeconomic variables, generally hard to find in other databases. Although extensive studies linking socioeconomic variables and adherence to a specific lipid-lowering agent exist [32, 33], they failed to explore the relationship between socioeconomic factors and the use of all types of lipid-lowering medications, which included initiation of therapy.

Conclusion

The objectives of the Healthy People initiative have changed over time, having focused initially on increasing cholesterol screening and subsequently on increasing treatments for patients with uncontrolled hyperlipidemia. This study serves as an evidence in the transition between these two focuses by highlighting factors significant for hyperlipidemia therapy. Moreover, this study draws its conclusions from real-world data obtained through controlled analysis. Beyond merely addressing the significance of a variety of socioeconomic factors for use of hyperlipidemia therapy, this study isolates certain particularly significant factors while controlling for other factors. In doing so, it provides data essential for prioritizing interventions by health policy makers.

23 Apr 2021

PONE-D-20-39424

Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: A Theoretical Approach

PLOS ONE

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study describes a theoretical approach used to identify predisposing and enabling factors which impact use of lipid lowering drugs in USA population. Authors adapted the Andersen Behavioral Model. The study analyzed associations among socioeconomic factors and the use of antihyperlipidemic agents using data from the 2018 Medical Expenditure Panel Survey. The study aim is not novel and does not add any new knowledge. However, it does confirm previously found associations. There are many problems with this study.

1. Authors stated that (line 84)…”no study has explored access to lipid-lowering medications for patients with high blood cholesterol in the United States”. This is not entirely true. Those studies below addressed similar questions:

• Navar AM, Taylor B, Mulder H, Fievitz E, Monda KL, Fievitz A, Maya JF, López JAG, Peterson ED. Association of Prior Authorization and Out-of-pocket Costs With Patient Access to PCSK9 Inhibitor Therapy. JAMA Cardiol. 2017 Nov 1;2(11):1217-1225. doi: 10.1001/jamacardio.2017.3451. PMID: 28973087; PMCID: PMC5963012.

• Whayne TF. Outcomes, Access, and Cost Issues Involving PCSK9 Inhibitors to Lower LDL-Cholesterol. Drugs. 2018 Mar;78(3):287-291. doi: 10.1007/s40265-018-0867-9. PMID: 29396831.

• Salami JA, Warraich HJ, Valero-Elizondo J, Spatz ES, Desai NR, Rana JS, Virani SS, Blankstein R, Khera A, Blaha MJ, Blumenthal RS, Katzen BT, Lloyd-Jones D, Krumholz HM, Nasir K. National Trends in Nonstatin Use and Expenditures Among the US Adult Population From 2002 to 2013: Insights From Medical Expenditure Panel Survey. J Am Heart Assoc. 2018 Jan 22;7(2):e007132. doi: 10.1161/JAHA.117.007132. PMID: 29358195; PMCID: PMC5850149.

Notably, Salami et al., (2018) were using the same data base for their analysis. None of the above refs were cited.

2. Another problem with the study presentation. Authors claimed in the title that the study is a theoretical approach, while it is a cross-sectional data analysis ( indicated in Methods). So , the title is confusing. There is no information about the study type in the abstract. Cross -sectional type of study should be reflected clearly. The whole study should be adjusted to the cross-sectional type. Discussion should accent this.

3. It is indicated (line 95) that “The MEPS sample is a subsample of the National Health Interview Survey (NHIS) that the National Center for Health Statistics conducts.” – however, there is no link to the data. Is it publicly available data? Or access was granted? It is not indicated; no links provided.

4. Reference presentation is not appropriate/correct the reference list according to the journal requirements.

5. Study limitations are missing and should be described.

Reviewer #2: The manuscript by Alfaifi et al "Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: A Theoretical Approach." performed important theoretical study and relevant to the current scenario. The design and organization of the manuscript is well and noted worthy. authors used good English. I recommend the manuscript for publication in current form.

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Reviewer #1: No

Reviewer #2: Yes: NAGENDRA YARLA

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27 Jun 2021

Dear Academic Editor: Olga A Sukocheva

Thank you for giving me the opportunity to submit a revised draft of my manuscript titled “Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: Application of Theoretical Framework” to PLOS ONE.

I appreciate the time and effort that you and the reviewers dedicated to providing your valuable feedback on my manuscript. I am grateful to the reviewers for their insightful comments on this paper. I have been able to incorporate changes to reflect most of the suggestions provided by the reviewers. I have highlighted these changes in the manuscript.

Here is a point-by-point response to the reviewers’ comments and concerns.

Comments from Reviewer 1

Comment 1: The study aim is not novel and does not add any new knowledge. However, it does confirm previously found associations. There are many problems with this study.

1. Authors stated that (line 84) …”no study has explored access to lipid-lowering medications for patients with high blood cholesterol in the United States”. This is not entirely true. Those studies below addressed similar questions:

• Navar AM, Taylor B, Mulder H, Fievitz E, Monda KL, Fievitz A, Maya JF, López JAG, Peterson ED. Association of Prior Authorization and Out-of-pocket Costs With Patient Access to PCSK9 Inhibitor Therapy. JAMA Cardiol. 2017 Nov 1;2(11):1217-1225. doi: 10.1001/jamacardio.2017.3451. PMID: 28973087; PMCID: PMC5963012.

• Whayne TF. Outcomes, Access, and Cost Issues Involving PCSK9 Inhibitors to Lower LDL-Cholesterol. Drugs. 2018 Mar;78(3):287-291. doi: 10.1007/s40265-018-0867-9. PMID: 29396831.

• Salami JA, Warraich HJ, Valero-Elizondo J, Spatz ES, Desai NR, Rana JS, Virani SS, Blankstein R, Khera A, Blaha MJ, Blumenthal RS, Katzen BT, Lloyd-Jones D, Krumholz HM, Nasir K. National Trends in Nonstatin Use and Expenditures Among the US Adult Population From 2002 to 2013: Insights From Medical Expenditure Panel Survey. J Am Heart Assoc. 2018 Jan 22;7(2):e007132. doi: 10.1161/JAHA.117.007132. PMID: 29358195; PMCID: PMC5850149.

Notably, Salami et al., (2018) were using the same data base for their analysis. None of the above refs were cited.

Thank you for pointing this out.

We agree that the novelty statement might be strong despite the fact that the examples are articles that looked at a particular antinyperlipidemic agent rather than the whole group. To address the issue, we modified the statement:

In line 84: “Until now, no study has explored access to lipid-lowering medications for patients with high blood cholesterol in the United States” changed to “Until now, limited number of studies have explored access to lipid-lowering medications for patients with high blood cholesterol in the United States without a theoretical framework.”

Comment 2: Another problem with the study presentation. Authors claimed in the title that the study is a theoretical approach, while it is a cross-sectional data analysis (indicated in Methods). So, the title is confusing. There is no information about the study type in the abstract. Cross -sectional type of study should be reflected clearly. The whole study should be adjusted to the cross-sectional type. Discussion should accent this.

Thank you for bringing this up; it is true that the wording “theoretical approach” in the title might cause a confusion for the readers. To address this issue we have made two major modifications:

• We changed the title from “Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: Theoretical Approach” to “Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: Application of a Theoretical Framework”

• In the abstract (Line 29): We modified the following sentence: “A theoretical approach with which to identify patients’ predisposing, enabling, and need factors was adapted from the Andersen Behavioral Model” to “This is a cross sectional design study that applied the Andersen Behavioral Model to identify patients’ predisposing, enabling, and need factors.”

Comment 3: It is indicated (line 95) that “The MEPS sample is a subsample of the National Health Interview Survey (NHIS) that the National Center for Health Statistics conducts.” – however, there is no link to the data. Is it publicly available data? Or access was granted? It is not indicated; no links provided.

As we worked with MEPS for an extended period of time, we assumed all readers would have similar background. For clarification, MEPS is publicly available data, and the sample is a subsample of the National Health Interview Survey (NHIS). The link for the two datasets are publicly available.

In the manuscript, we changed the sentence to (line 98) “The MEPS data is publicly available and sponsored by The Agency for Healthcare Research and Quality.”

Comment 4: Reference presentation is not appropriate/correct the reference list according to the journal requirements.

We apologize for the formatting errors (mentioned in comment 4). We have made the necessary changes to follow the reference style required by PLOS ONE. Moreover, we utilized a Scientific English editor to validated the manuscript style.

List of modifications for the references:

• Used the recommended abbreviations for journals outlined in the ICMJE sample references.

• Replaced all references that included bracket “[Internet]” with the actual links

• Modified reference 9 to: Grundy SM, Stone NJ, Bailey AL, Beam C, Birtcher KK, Blumenthal RS, Braun LT, De Ferranti S, Faiella-Tommasino J, Forman DE, Goldberg R. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Journal of the American College of Cardiology. 2019 Jun 25;73(24):e285-350.

• Modified reference 12 to: Berger JH, Chen F, Faerber JA, O'Byrne ML, Brothers JA. Adherence with lipid screening guidelines in standard-and high-risk children and adolescents. American Heart Journal. 2021 Feb 1;232:39-46.

• Modified reference 20 to: Etats-Unis. Department of health and human services, Centers for Disease Control and Prevention, National Center for Health Statistics. Healthy people 2010: Final review. US Government Printing Office; 2012.

Comment 5: Study limitations are missing and should be described.

Addressed, the following paragraph was added at the end of the discussion session

“This study had some limitations; the cross-sectional design of MEPS—by its very nature—describes a limited period: the results of this study cannot be generalized to years other than 2018. Moreover, establishing causal relationships from a cross-sectional design presents a special set of difficulties. However, these limitations were not thought so great as to outweigh MEPS data’s ability to supply various clinical and socioeconomic variables, generally hard to find in other databases. Although extensive studies linking socioeconomic variables and adherence to a specific lipid-lowering agent exist [32-33], they failed to explore the relationship between socioeconomic factors and the use of all types of lipid-lowering medications, which included initiation of therapy.”

Comments from Reviewer 2

Comment 1: The manuscript by Alfaifi et al "Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: A Theoretical Approach." performed important theoretical study and relevant to the current scenario. The design and organization of the manuscript is well and noted worthy. authors used good English. I recommend the manuscript for publication in current form.

Thank you for endorsing the manuscript. To ensure that the language is better, we have submitted the manuscript to a Scientific Manuscript Editing Service for academic papers.

Comments from editorial

It is necessary to provide more details in 1- the introduction and discussion section in order to demonstrate the novelty of your research and potential future application of your research outcome. 2- More relevant references should be included. 3- Although the research design is appropriate the methods should be adequately described to indicate what is the main difference of your study from the previous similar analyses.

1. We would like to thank the editors and the reviewers for their comments. In response to the first point raised by the editor, we added more details to the discussion to ensure the novelty of the study (Line 240 -249)

2. As an extension to the first point, we added relevant references–suggested by reviewer 1 in the discussion (References number 32 & 33).

3. An additional statement was added under the Methods study design (line: 112-114): “The present study provided an unbiased overview of all groups of therapy used for hyperlipidemia.”

Additional points:

• The guidelines recommend that abbreviations may be used only if the term is mentioned more than 3 times. Line 69 was changed to “β-Hydroxy β-methylglutaryl-CoA” instead of “HMG CoA reductase inhibitor”

• We used “The U.S.” consistently throughout the manuscript

I look forward to hearing from you regarding my revised submission and in of further questions and comments you may have.

Sincerely,

Abdullah Alfaifi

Assistant Professor

Department of Clinical Pharmacy

Pharmacoeconomics and Outcome Research

Tel: +966 11-588- 6058

E-mail: a.alfaifi@psau.edu.sa

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

23 Jul 2021

Barriers in utilizing lipid-lowering agents in non-institutionalized population in the U.S.: Application of a theoretical Framework

PONE-D-20-39424R1

Dear Dr. Alfaifi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Olga A Sukocheva, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I am satisfied with the revised version of this manuscript; authors addressed all my suggestions properly.

Reviewer #2: The manuscript by Alfaifi et al "Barriers in Utilizing Lipid-Lowering Agents for U.S. Civilians Non-Institutionalized Population: A Theoretical Approach." performed important theoretical study and relevant to the current scenario. The design and organization of the manuscript is well and noted worthy. authors used good English. I recommend the manuscript for publication in current form. Authors addressed questions and there is no concerns from my side.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: NAGENDRA YARLA

28 Jul 2021

PONE-D-20-39424R1

Barriers in utilizing lipid-lowering agents in non-institutionalized population in the U.S.: Application of a theoretical Framework

Dear Dr. Alfaifi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Olga A Sukocheva

Academic Editor

PLOS ONE