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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