Socioeconomic Disparities in Arthritis


Study

Reference

Data (country)

Size

Adjusted for

SES variables

Results

Leigh 1991

Leigh and Fries (1991a)

NHANES-I, QES73, SDW78, NHIS86 (USA)
    
Hannan 1992

Hannan et al. (1992)

NHANES-I (USA)

6880

Income, BMI, smoking, knee injury

Education: HS, <HS

Greater risk among <HS than ≥HS

Income

Wang 2000

Peter Wang et al. (2000)

NPHS (Canada)

39,240

Education, BMI

Income

Greater prevalence in group with low income based on family size (e.g., <$15,000 for one- or two-person family) vs. not-low income participants

Education

Busija 2007

Busija et al. (2007)

VPHS (Australia)

7500

BMI
  
Callahan 2008

Callahan et al. (2008)

NC-FM-RN (NC, USA)

7306
   
Cañizares 2008

Cañizares et al. (2008)

Community health survey (Canada)

127,513
   
Grotle (2008)

Grotle et al. (2008)

Community survey (Norway)

3266
   
Cunningham 2011

Cunningham (2011)

NATSIHS (Australia)

18,340
   
Brennan 2012

Brennan and Turrell (2012)

HABITAT (Australia)

10,757
 
Education
 
Income

Area SES

Baldassari 2013

Baldassari et al. (2013a)

NC-FM-RN (NC, USA)
 
Age, sex, race

Count of low education, non-homeowner-ship and low SES occupation
 
Count of low maternal: education, non-parental homeownership and low-SES paternal occupation

Anderson 1988

Anderson and Felson (1988)

NHANES-I (USA)

5193
 
Income: (continuous scale)

KNEE OA

Decreased risk with $5000/year income increments, similarly for both men and women (OR = 0.8). Not significant in fully adjusted models

Education: <8 years, 9–12 years, >12 years

Decreased risk per increase in education category. OR = 0.7 for men, OR = 0.8 for women. Not significantin fully adjusted models

Hannan 1992

Hannan et al. (1992)

NHANES-I (USA)

6880

Age, race, sex, smoking

Education

KNEE OA

Greater prevalence with fewer years of education,for r-kOA (lowest vs. highest OR = 1.5) and s-kOA (lowest vs. highest OR = 1.3). Explained by BMI for r-kOA but not s-kOA

Tepper 1993

Tepper and Hochberg (1993)

NHANES-I (USA)

2358

Age, race, sex, marital status, other SES variable

Education

HIP OA

Greater prevalence in <12 years of schooling vs. ≥12 years, slightly short of significance at α = 0.05 (OR = 1.64). Possibly stronger association among men

Income

No significant associations, imprecise estimates show possible U-shaped relation between higher family income and hip OA

Andrianakos 2006

Andrianakos et al. (2006)

Population-based study (Greece)

8740

Age, gender,

Education: ≤12 years, >12 years

KNEE, HIP, AND HAND OA

Greater risk of knee OA for ≤12 years vs. >12 years (OR = 2.8) but not for hand or hip OA

Occupation: non-manual, others

Lower risk for hand OA for non-manual occupations vs. others (OR = 0.6), but not hip OA or knee OA

Callahan 2008

Callahan, Cleveland, et al., (2011)

Johnston County OA project (USA)

3552

Age, gender, race, BMI, physical activity

Education: <12 years, ≥12 years

KNEE OA

Greater risk in <12 years of schooling vs. ≥12 years for unilateral (OR = 2.1) and bilateral r-kOA, and symptomatic unilateral (OR = 2.2) and bilateral r-kOA

Occupation: managerial, others

Greater risk for non-managerial vs. managerial, for r-kOA (OR = 1.4) and s-kOA (OR = 1.5). Explained by other SES variables

Area poverty: high, medium, low

Greater risk in medium and high poverty vs. low poverty. OR for High vs. low poverty = 1.9 (r-kOA) and 1.4 (s-kOA)

Callahan 2010

Callahan et al. (2010)

Johnston County OA project (USA)

2627

Age, race/ethnicity, stratified by gender

Education: <12 years, ≥12 years

KNEE OA

Greater prevalence for <12 years vs. ≥12 years, for r-kOA (women only: OR = 1.6) and s-kOA (Men: OR = 1.55, Women: OR = 1.9). Unexplained by BMI, smoking, alcohol use, previous knee injury, hormone replacement therapy

Cleveland 2013

Cleveland et al. (2013)

Johnston County OA project (USA)

3087

Age, gender, race, BMI, smoking, prior hip injury, workplace physical demands

Education: <12 years, ≥12 years

HIP OA

Greater risk in <12 years of schooling vs. ≥12 years for unilateral (OR = 1.4) and bilateral s-hOA (OR = 2.0), and for bilateral s-hOA (OR = 1.3)

Occupation: managerial, others

Greater risk for non-managerial vs. managerial, for r-hOA (OR = 1.4) and s-hOA (OR = 1.5). Explained by other SES variables

Area poverty: high, medium, low

Greater risk in medium and high poverty vs. low poverty. Unilateral/bilateral High vs. low OR = 1.3/2.0 (r-kOA) and 1.6/NS (s-kOA)

Rodriguez-Amado 2014

Rodriguez-Amado et al. (2014)

Population-based study (Mexico)

17,566
  
ANY OA


NHANES National Health and Nutrition Examination Survey





Self-Reported Arthritis


Ascertainment of arthritis can be challenging in large-scale studies, and self-reported case definitions are often used to facilitate the evaluation of disease burden. Case definitions used in most studies involve participant reports of any prior receipt of an arthritis or rheumatic disease diagnosis from a health professional; self-reported chronic arthritis symptoms have also been used, rarely as a stand-alone criterion and typically together with a self-reported doctor diagnosis. There is evidence that self-reported case definitions for arthritis have satisfactory sensitivity for population surveillance purposes, but suffer from low specificity, particularly among individuals less than 65 years old (Bombard, Powell, Martin, Helmick, & Wilson, 2005). Nevertheless, there is no evidence that instrument validity for self-reported arthritis definitions varies by SES, as could systematically bias estimates of the SES and self-reported arthritis association. To the extent that most self-reported arthritis involves OA of the hips, knees, or hands, the evidence for its differential prevalence by SES complements that presented in our section on radiographic OA.

We summarize some of the work on socioeconomic differences in the risk of self-reported arthritis in Table 6.2. These studies span decades, geographic regions, and demographic groups, yet almost unanimously find meaningful differences in the risk of self-reported arthritis by a number of socioeconomic characteristics, including education, income, neighborhood disadvantage, or occupational class. There is equivocal evidence for effect-measure modification by race/ethnicity. Cunningham and colleagues notably found gradient patterns of increased self-reported arthritis susceptibility with lower SES, but only among non-indigenous participants in a sample of Australian participants (Cunningham, 2011); in comparison, data from a cohort study in rural North Carolina (USA) did not suggest significantly different patterns of inequities between Whites and African Americans (Callahan et al., 2008).


Table 6.2
Overview of socioeconomic disparities in self-reported doctor-diagnosed arthritis prevalence












































































































































Study

Reference

Data (country)

Size

Adjusted for

SES variables

Results

Hannan 1992

Hannan et al. (1992)

Population health survey: NHANES-I (USA)

6880

Age, gender, race, smoking

Education: 0–8 years, 9–11 years, 12 years, ≥13 years

Increasing risk with lower educational category. Lowest vs. highest OR = 1.51. Unchanged by further adjustments for BMI and knee injury

Wang 2000

Peter Wang et al. (2000)

Population health survey: NPHS (Canada)

39,240

Age, gender, ethnic group, other SES variables

Education: <secondary, ≥secondary

No difference by low education status

Income: low for, family size, not low

Greater risk in low income group than not-low group (OR = 1.14)

Occupation: unskilled, semiskilled, professional

No meaningful difference in risk by occupation

Busija 2007

Busija et al. (2007)

Population health survey: VPHS (Australia)

7500

Age, gender, BMI, area of residence, other SES variables

Education: primary, secondary, tertiary

No meaningful independent associations

Income: <$A 20 K, 20–40 K, 40–60 K, >60 K

Increasing risk with decreasing income; vs. highest category, ORs = 0.8, 0.6 and 0.5 respectively

Occupation: professional, others

No meaningful independent associations

Callahan 2008

Callahan et al. (2008)

Primary-care patients: NC-FM-RN (NC, USA)

7306

Age, gender, BMI, stratified by race.

Education: <12 years, 12 years, ≥12 years

Greater risk in <12 years vs. >12 years; OR = 1.55 for Whites and 1.92 for African Americans

Area poverty: low %, medium %, high %

No independent main effects, but meaningful interaction of greatest poverty with highest education category: OR = 1.55 for Whites, 2.06 for African Americans

Cañizares 2008

Cañizares et al. (2008)

Community health survey (Canada)

127,513

Age, gender, race, smoking, physical activity, immigration status,, area characteristic, other SES variables

Education: <secondary, secondary, >secondary

No meaningful independent association

Income: <$A 20 K, 20–40 K, 40–60 K, ≥60 K

Increasing risk in decreasing income categories; vs. ≥60 K, OR = 1.49, 1.26, and 1.13, respectively

Area poverty: % low-SES

Greater risk with increasing % of low-income families (OR = 1.3 for 10 % increase), but not with increasing % of low-education families

Grotle 2008

Grotle et al. (2008)

Community survey (Norway)

3266

Age, gender

Education: ≤9 years, 9–12 years, >12 years

Uses selfreported osteoarthritis rather than any arthritis

Evenly greater self-reported OA risk for lower two education categories vs. >12 years, for any OA (OR ≈ 2.1), hip OA (OR ≈ 2.8), knee OA (OR ≈ 2.3), and hand OA (OR ≈ 1.5)

Cunningham 2011

Cunningham (2011)

Population health survey NATSIHS (Australia)

18,340

Age, gender, stratified by indigenous status

Education: <12 years, ≥12 years, or no degree, certificate, diploma, university

Associations only found among nonindigenous participants, except for greater risk for lowest vs. highest income quartile among indigenous (OR = 1.6)

Lower risk for ≥12 years than less than years (OR = 0.6)

Decreasing risk with higher categories of education than no degree. University vs. no degree OR = 0.5

Income: quintiles

Increasing risk with lower income quintiles than Q3-5. Q1 vs. Q3-5 OR = 2.1

Area poverty: quintiles

Increasing risk with lower area poverty. Q1 (poorest) vs. Q5 (richest) OR = 1.7

Housing tenure

No meaningful association

Brennan 2012

Brennan and Turrell (2012)

Population-based cross-sectional study: HABITAT (Australia)

10,757
 
Education: Secondary, Certificate, Diploma, Bachelor

Greater disease in categories lower than highest education, similar in all three lower categories (OR ≈ 1.3)

Income: <$A 26 K, 26–42 K, 42–73 K, 73–130 K, >130 K

Progressively higher risk with decreasing income category: respectively, OR = 1.96, 1.75, 1.51, 1.28

Occupation: blue collar, white collar, professional

No meaningful independent association with work status among the employed

Area poverty: quintiles

Greater risk among people in quintile 2 or 3 (OR ≈ 1.2) and quintile 1 (lowest SES, OR = 1.42) vs. quintile 5 (highest SES)

Baldassari 2013

Baldassari, Cleveland, and Callahan (2013b)

Primary-care patients: NC-FM-RN (NC, USA)

1276

Age, sex, race

Current SES: Count of low education, non-homeowner-ship and low SES occupation

Increasing risk of self-reported arthritis with increasing count of low-SES factors. Not explained by childhood SES or BMI: lowest vs. highest OR = 2.08 in fully adjusted models

Count of low maternal: education, non-parental homeownership and low-SES paternal occupation

Increasing risk with higher count of childhood low-SES factors. Lowest vs. highest SES difference remained significant after adjusting for current SES and BMI (OR = 1.39)


NHANES-I National Health and Nutrition Examination Survey, QES Quality of Employment Survey, SDW Survey of Disability and Work, NHIS National Health Interview Survey, NPHS National Population Health Survey, VPHS Victorian Population Health Survey, NC-FM-RN North-Carolina Family-Medicine Research Network, NATSIHS National Aboriginal and Torres Strait Islander Health Survey, HABITAT How Areas in Brisbane Influence Health and Activity study



Rheumatoid Arthritis


With a prevalence between 0.5 and 1 %, rheumatoid arthritis (RA) is the most common autoimmune disorder; women represent two thirds of all cases (Gabriel, 2001) and the disease typically occurs between the age of 50 and 75. Current genetic heritability estimates for RA do not exceed 50 % (Frisell et al., 2013), leaving ample room for modifiable determinants which, with the exception of smoking (Silman, Newman, & Macgregor, 1996), remain largely unknown.

We provide an overview of studies on socioeconomic differences in RA risk in Table 6.3. While early studies found no clear associations of socioeconomic status with RA development (Bankhead et al., 1996; Uhlig et al., 1999), more recent work consistently suggests that people with low SES are at an increased susceptibility for RA. Intriguing data further indicate that socioeconomic disadvantage chiefly increases susceptibility to seropositive disease (Bengtsson et al., 2005; Pedersen et al., 2006), as characterized by rheumatoid factors, supporting the increasingly adopted notion that seropositive and seronegative RA constitute etiologically distinct phenotypes.


Table 6.3
Overview of studies of socioeconomic disparities in rheumatoid arthritis risk
































































































Study

Reference

Data (country)

Size

Adjusted for

SES variables

Results

Bankhead 1996

Bankhead et al. (1996)

Population-based register NOAR (USA)

687

Stratified by gender

Five census-level variables

No strong correlation between SES variables and arthritis incidence (r s between 0 and 0.3)

Uhlig 1999

Uhlig, Hagen, and Kvien (1999)

County RA register (Norway)

361 cases, 5851 controls

Age, gender, smoking

Education

Not associated with RA risk

Olsson 2001

Olsson, Skogh, and Wingren (2001)

Single hospital records (Denmark)

281 cases, 507 controls

Age, smoking, high-risk occupation

Education

Lower incidence for secondary/upper secondary and university vs. compulsory school only (RR ≈ 0.5). Similar disparities among men and women

Jaakola and Gissler 2004

Jaakkola and Gissler (2005)

1987 national birth cohort, (Finland)

56,632

Age (birth cohort), gender, birth order, maternal age, marital status, current SES index

Maternal occupation

Increased risk of inflammatory polyarthropathies (incl. RA) (OR = 2.11) and juvenile RA (OR = 2.12) for blue-collar vs. upper white-collar maternal occupation. Imprecise estimates; not statistically significant

Bengtsson 2005

Bengtsson et al. ( 2005)

Population-based case-control study EIRA (Sweden)

930 cases, 1126 controls

Age, residential area, smoking

Education

Greater incidence of RA among participants in both educational categories below university degree (RR ≈ 1.7), similarly among men and women. Associations stronger for RF-positive RA than for RF-negative RA

Occupation

Higher RA incidence among women in the manual occupational class vs. non-manual (RR ≈ 1.3). Associations stronger for RF-positive RA than for RF-negative RA

Pedersen 2006

Pedersen et al. (2006)

Nationwide hospital records over 5 years (Denmark)

515 cases, 769 controls

Gender, year of birth, year of diagnosis, place of residence

Education

Lower risk with greater education in graded pattern (linear trend p < 0.001, highest vs. lowest education RR ≈ 0.4). Only observed for RF-positive RA

Current affluence

Lower risk in middle and most affluent thirds vs. least affluent thirds (OR 0.9 and 0.66), not significant at α = 0.05

Lower risk in middle and most affluent thirds vs. least affluent thirds (OR 0.90 and 0.66), not significant at α = 0.05

Affluence during childhood

Schneider 2006

Schneider, Schmitt, and Richter (2006)

National Health survey (Germany)

6491

Age, sex

Occupation

Top-level office workers, and white-collar vs. manual OR = 0.27 and 0.54. Unexplained by lifestyle factors and other sociodemographic variables

Education

Highest category and high school vs. no high school OR = 0.5 and 0.72

Social status

Upper class and middle class vs. Lower class OR = 0.54 and 0.86

Bergstrom 2011

Bergström et al. (2011)

Citywide Preventative screening program (Sweden)

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Apr 9, 2017 | Posted by in PSYCHOLOGY | Comments Off on Socioeconomic Disparities in Arthritis

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