| Literature DB >> 35794906 |
Ernest R Vina1, Philip H Tsoukas2, Shahrzad Abdollahi2, Nidhi Mody2, Stephanie C Roth3, Albert H Redford4, C Kent Kwoh4.
Abstract
Background: Racial and ethnic disparities in osteoarthritis (OA) patients' disease experience may be related to marked differences in the utilization and prescription of pharmacologic treatments.Entities:
Keywords: African Americans; Hispanics; ethnicity; medications; osteoarthritis; race; utilization
Year: 2022 PMID: 35794906 PMCID: PMC9251972 DOI: 10.1177/1759720X221105011
Source DB: PubMed Journal: Ther Adv Musculoskelet Dis ISSN: 1759-720X Impact factor: 3.625
Figure 1.Flow diagram.
Basic characteristics of studies included.
| Investigator(s) | Geographic location | Study population | Mean Age (years) | Sex (%female) | # Study participants by race/ethnicity | Race/ethnicity measure | Utilization measure | Study design (study time period) |
|---|---|---|---|---|---|---|---|---|
| Coulton | Ohio | Community sample | ~72 | ~70 | WH (112), AA (105), HIS (100) | Self-report | Survey | Cross-sectional (N/A) |
| Ausiello and Stafford
| All states in the USA | Community sample | N/A | 68.8 | WH (1433), Non-WH (295) | Physician report or medical record | Survey | Cohort (1989–1991, 1992–1994, 1995–1998) |
| Mikuls | Alabama | Community sample | ~65 | ~72 | WH (852), AA (528) | Self-report | Survey | Cross-sectional (2001) |
| Dominick | North Carolina | Veterans | 61 | 5 | WH (1612), AA (861) | Medical record | Pharmacy database | Cross-sectional (1998–1999) |
| Dominick | All states in the USA | Veterans | 61 | 5 | WH (3410), AA (686), HIS (191) | Medical record | Pharmacy database | Cohort (2000) |
| Dominick | North Carolina | Veterans | 64 | 9 | WH (141), AA (61) | Medical record | Survey | Cross-sectional (2002–2003) |
| Dominick | North Carolina | Veterans | 60 | 4 | WH (1622), AA (857) | Medical record | Pharmacy database | Cross-sectional (1998–1999) |
| Herman | New Mexico | Community sample | N/A | 67 | WH (204), HIS (218) | Medical record | Survey | Cross-sectional (2000–2001) |
| Katz and Lee
| Multiple states in the USA | Community sample | 61 | 68 | WH (220), AA (322), HIS (317) | Self-report | Survey | Cross-sectional data from randomized controlled trials (N/A) |
| Albert | Pennsylvania | Community sample | ~73 | ~60 | WH (267), AA (284) | Self-report | Survey | Cross-sectional (2001–2002) |
| Marcum | Pennsylvania, Tennessee | Community sample | 79 | 66 | WH (390), AA (262) | Self-report | Survey | Cross-sectional (2002–2003) |
| Yang | Multiple states in the USA: Maryland, Ohio, Pennsylvania, and Rhode Island | Community sample | >65 | ~63 | WH (2075), AA (508) | Self-report | Survey | Cross-sectional data from cohort study (2004–2006) |
| Kingsbury | Multiple states in the USA: Maryland, Ohio, Pennsylvania, and Rhode Island | Community sample | ~62 | ~56 | WH(701), Non-WH (286) | Self-report | Survey | Cohort (N/A) |
| Lapane | Multiple states in the USA: Maryland, Ohio, Pennsylvania, and Rhode Island | Community Sample | ~65 | ~58 | WH (1,757), AA (~429), Other (~71) | Self-report | Survey | Cross-sectional data from cohort study (2004–2006) |
| Abbate | North Carolina | Community sample and veterans | ~63 | ~52 | WH (723), Non-WH (464) | Unknown | Survey | Cross-sectional data from randomized controlled trials (N/A) |
| Consson | Northwest USA | Community sample | ~66 | ~58 | WH (573), HIS Non-WH (48) | Medical record | Pharmacy database | Cohort (2016–2017) |
| Vina | Arizona | Community sample | ~63 | ~71 | WH (204), HIS (130) | Self-report | Survey | Cross-sectional (2015–2018) |
| Khoja | All states in the USA | Community Sample | 64 | ~64 | WH (1902), AA (237). | Physician report or medical record | Survey | Cross-sectional (2007–2015) |
| Vina | Arizona | Community sample | ~64 | 70 | Non-HIS (228), HIS (121) | Self-report | Survey | Cross-sectional (2015–2018) |
| Vina | Pennsylvania | Veterans | 64 | 27 | WH (247), AA (270) | Self-report | Survey | Cross-sectional data from randomized controlled trial (2018) |
| Wu | North Carolina | Community sample | N/A | N/A | WH(74769), AA (27117), HIS (1479), Asians (1479) | Medical record | Pharmacy database | Cohort (2013–2020) |
AA, African-American; HIS, Hispanic; WH, White.
Studies that investigated race/ethnic differences in the use of non-steroidal anti-inflammatory drugs (NSAIDs) for OA.
| Investigator(s) | Findings | Variables adjusted for | Findings after adjustment |
|---|---|---|---|
| Ausiello and Stafford
| NS: Non-WHs (50.9%) ≈ WHs (45.1%), 1989–1991. | Age, sex, patient insurance, and physician specialty | Race difference in 1992–1994 persisted. Lack of association in other years (1989–1991, 1995–1998) persisted. |
| Mikuls | COX-2: ~25% AAs ≈ ~25% WHs | Marital status, education, joint swelling/stiffness, and rheumatoid arthritis diagnosis | Lack of association persisted |
| Dominick | COX-2: AAs (4.1%) < WHs (7.4%) | Age, sex, service connection, and having arthroplasty (5 years) | Race differences persisted |
| Dominick | COX-2: AAs (8.9%), HISs (7.3%) < WHs (10.2%) | Age, sex, geographic location, comorbidities, history of GI bleed, use of anticoagulants, and use of corticosteroids | COX-2: Ethnic difference persisted, but race difference ( |
| Dominick | COX-2: AAs (13.1%) ≈ WHs (18.4%) | Age, gender, education, WOMAC, years with OA, and number of affected joints | Lack of associations persisted |
| Albert | COX-2: AAs (9.7–29.5%) ≈ WHs (20.0–34.4%) | Gender, severity of arthritis, age, education, pain, and access to prescription | COX-2: Race difference did not persist |
| Yang | COX-2: AAs (5.7%) < WHs (9.3%) | Unadjusted | N/A |
| Kingsbury | COX-2: Non-WHs (6.6%) < WHs (11.7%) | Unadjusted | N/A |
| Abbate | NS: Non-WH race not associated with NS use (multivariable-adjusted model) | Age, sex, income, health, body mass index, WOMAC, OA symptoms, and knee/hip OA | Lack of associations persisted |
| Vina | Over-the-counter NS: HISs (52.9%) < WHs (66.3%) | Age, sex, education, and private medical insurance | Ethnic differences did not persist |
| Khoja | AA race not associated with NS prescription. | Clinical characteristics, patient demographics, physician characteristics, and practice characteristics | Ethnic difference in NS prescription (by orthopedists) did not persist |
AA, African-American; COX-2, cyclooxygenase-2 selective NSAID; GI, gastrointestinal; HIS, Hispanic; NS, non-selective (not cyclooxygenase-2 selective) NSAID; NSAIDs, non-steroidal anti-inflammatory drugs; OA, osteoarthritis; WH, White; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.
Studies that investigated race/ethnic differences in the use of opioids for OA.
| Investigator(s) | Findings | Variables adjusted for | Findings after adjustment |
|---|---|---|---|
| Mikuls | AAs (~5%) ≈ WHs (~5%) | Gender, education, joint swelling, comorbidity, rural residence, and income | Lack of association persisted |
| Dominick | AAs (32.6%) < WHs (40.1%) | Age, sex, service connection, having arthroplasty (5 years) | Race difference persisted |
| Dominick | AAs (14.8%) ≈ WHs (21.3%) | Age, gender, education, WOMAC, years with OA, and number of affected joints | Lack of association persisted |
| Dominick | AAs (39.0%) < WHs (47.3%) | Gender and service connection | Race difference persisted |
| Albert | AAs (3.2–17%) ≈ WHs (6.2–14.5%) | Gender and severity of arthritis (stratified only) | N/A |
| Marcum | AA race not associated with opioid use | OA pain severity, age, sex, site, education, osteoporosis, health status factors (osteoporosis and cancer), health, body mass index, and access to healthcare | Lack of association persisted |
| Yang | AAs (3.9%) ≈ WHs (2.6%) | Unadjusted | N/A |
| Kingsbury | Non-WHs (4.9%) ≈ WHs (2.7%) | Unadjusted | N/A |
| Consson | HIS non-WHs (27.1%) ≈ WHs (27.6%) | Unadjusted | N/A |
| Vina | HISs (30.5%) ≈ non-HISs (27.5%) | Unadjusted | N/A |
| Khoja | AA race associated with > likelihood of opioid prescription (by primary care physician). | Clinical characteristics, patient demographics, physician characteristics, and practice characteristics | Race difference in opioid prescription (by primary care physician) did not persist |
AA, African-American; HIS, Hispanic; OA, osteoarthritis; WH, White; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.
Studies that investigated race/ethnic differences in the use of other conventional therapies for OA.
| Investigator(s) | Findings | Variables adjusted for | Findings after adjustment |
|---|---|---|---|
| Ausiello and Stafford
| ACE: Non-WHs (2.7%) ≈ WHs (5.1%), 1989–1991. | Age, sex, patient insurance, and physician specialty | Lack of association in all time periods (1989–1991, 1992–1994, 1995–1998) persisted. |
| Dominick | ACE: AAs (31.9%) ≈ WHs (29.2%) | Age, sex, service connection, and having arthroplasty (5 years) | Lack of association persisted |
| Dominick | ACE: AAs (18.0%) ≈ WHs (19.9%) | Age, gender, education, WOMAC, years with OA, and number of affected joints | Lack of association persisted |
| Yang | ACE: AAs (17.9%) > WHs (9.5%) | Unadjusted | N/A |
| Lapane | COR and HYA: AAs less likely than WHs to report use | Age, gender, income, radiographic severity, history of knee injury, WOMAC, quality of life, acetaminophen use, and chondroitin use | Race difference persisted |
| Kingsbury | ACE: Non-WHs (18.2%) > WHs (11.6%) | Unadjusted | N/A |
| Abbate | COR/HYA: Non-WH race not associated with intra-articular injection use (multivariable-adjusted model) | Age, sex, income, health, body mass index, WOMAC, OA symptoms, and knee/hip OA | Lack of associations persisted |
| Wu | COR: Knee injection, AAs (31.5%) & HISs (26.5%) < WHs (34.0%). Hip injection, AAs (14.5%) ≈ HISs (11.9%) ≈ WHs (15.0%). | Gender, age, substance use, medical insurance, rural/urban, and income | Race difference (in knee injection) and lack off association (in hip injection) persisted |
AA, African-American; ACE, Acetaminophen; COR, Corticosteroid joint injection; HIS, Hispanic; HYA, Hyaluronic acid joint injection; OA, osteoarthritis; WH, White; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.
Studies that investigated race/ethnic differences in the use of complementary and alternative medicines (CAMs) for OA.
| Investigator(s) | Findings | Variables adjusted for | Findings after adjustment |
|---|---|---|---|
| Coulton | VIT: AAs (5%) ≈ HISs (5%) ≈ WHs (5%) | Unadjusted (for VIT) | N/A |
| Mikuls | GLU/CHO: AAs (7%) < WHs (18%) | Age, gender, education, and joint swelling (for use of any CAM therapy) | Any CAM therapy: No race association |
| Herman | GLU: HISs (15.4%) < WHs (34.1) | Age, sex, education, income, duration of disease, disability, pain, arthritis helplessness, and medical skepticism | General patterns of ethnic differences similar but statistical significant effects somewhat different |
| Katz and Lee
| GLU/CHO: AAs (10.7%) ≈ HISs (9.8%) ≈ WHs (14.6%) | Sex, age, body mass index, pain severity, WOMAC function, WOMAC stiffness, and patient’s global assessment (for use of any CAM therapy) | Any CAM therapy: HISs < AAs and WHs < AAs |
| Albert | MIN/VIT: AAs (19.4–42.6%) < WHs (30.9–45.7%) | Gender and severity of arthritis (stratified only) | N/A |
| Yang | GLU: AAs (11.6%) < WHs (31.7%) | Unadjusted | N/A |
| Kingsbury | GLU/CHO: Non-WHs (24.5%) < WHs(47.4%) | Unadjusted | N/A |
| Vina | GLU/CHO: AAs (9.8–11.7%) < WHs (14.3–20.7%) | Recruitment site, age, WOMAC total, and comorbidities | Race difference in GLU/CHO use persisted. Lack of association in HER, and MIN/VIT use persisted |
AA, African-American; CAM, complementary and alternative medicines; CHO, chondroitin; GLU, glucosamine; HER, herbals; HIS, Hispanic; MIN, minerals; VIT, vitamins; WH, White; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.