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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

Objective

To examine cross-sectional baseline data from the Johnston County Osteoarthritis Project for the association between individual and community socioeconomic status (SES) measures with hip osteoarthritis (OA) outcomes.

Methods

We analyzed data on 3,087 individuals (68% white and 32% African American). Educational attainment and occupation were used as individual measures of SES. Census block group household poverty rate was used as a measure of community SES. Hip OA outcomes included radiographic OA and symptomatic OA in one or both hip joints. Multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the association of each hip OA outcome with each SES variable separately, and then with all SES measures simultaneously. Associations between hip OA outcomes and SES variables were evaluated for effect modification by race and sex.

Results

Living in a community of high household poverty rate showed independent associations with hip radiographic OA in one or both hips (OR 1.50, 95% CI 1.18–1.92) and bilateral (both hips) radiographic OA (OR 1.87, 95% CI 1.32–2.66). Similar independent associations were found between low educational attainment among those with symptomatic OA in one or both hips (OR 1.44, 95% CI 1.09–1.91) or bilateral symptomatic OA (OR 1.91, 95% CI 1.08–3.39), after adjusting for all SES measures simultaneously. No significant associations were observed between occupation and hip OA outcomes, nor did race or sex modify the associations.

Conclusion

Our data provide evidence that hip OA outcomes are associated with both education and community SES measures, associations that remained after adjustment for covariates and all SES measures.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

Osteoarthritis (OA), the most prevalent form of arthritis, is a painful and often disabling condition, currently affecting more than 27 million adults in the US [1, 2]. The most common forms of OA are knee OA and hip OA, which can significantly impact a person's mobility and sometimes necessitate surgical procedures, such as total joint replacement [3]. As such, OA is a major source of disability and can have a great impact on quality of life, including fatigue, psychological distress (i.e., depression, behavioral, and social outcomes), and reduced physical function [4]. Several factors place individuals at a higher risk of developing hip OA, including older age, female sex, high body mass index (BMI), previous hip injury, genetics or family history of OA, and lower levels of education or socioeconomic status (SES) [1, 2, 5-8].

Previous studies have shown associations between measures of SES such as educational attainment and occupation and the development of chronic illness and arthritis [9-14]. In particular, several studies have examined the relationship between lower levels of educational attainment and both OA prevalence and poorer health status outcomes [5, 13, 15-20]. Two of these studies have examined SES measures and radiographic OA of the knee [5, 21]. The first study evaluated the First National Health and Nutrition Examination Survey (NHANES-I; 1971–1975), noting that low educational attainment levels were associated with both radiographic OA and symptomatic OA of the knee; however, only knee symptomatic OA remained independently associated after controlling for occupation, age, race, obesity, and knee injury [5]. Additionally, our group assessed the relationship between lower educational attainment and knee radiographic OA and symptomatic OA in a cross-sectional sample of 2,627 non-Hispanic African Americans and whites in the Johnston County Osteoarthritis Project [21]. After adjusting for known risk factors, it was shown that lower educational attainment was associated with increased prevalence of knee symptomatic OA in both men and women, and with knee radiographic OA in women.

Few studies have examined associations between educational attainment and OA prevalence in the hip. Also using data from NHANES-I, Tepper and Hochberg examined the relationship between years of education (dichotomized as greater than and less than or equal to 12 years of school) and radiographic OA. Although univariate logistic regression analyses suggested that higher educational level was associated with hip radiographic OA, a multivariate model determined that this relationship was of borderline statistical significance [19]. In contrast, a study carried out in Norway reported increased prevalence of self-reported hip OA among those with fewer than 12 years of education [22]. Another recent Australian study reported a nonsignificant U-shaped association of total hip replacement with SES, which was defined as the Index of Relative Socio-Economic Disadvantage of the census district where one lived [23]. Although not specific to hip OA, an additional study by Brennan and Turrell reported that those living in the highest quintile of neighborhood disadvantage had higher rates of self-reported arthritis [24]. It appears that no other study has evaluated SES and hip OA specifically.

In addition to individual measures, community factors have also been found to play a role in the development of arthritis and other chronic illness [25-31]. Even after controlling for a person's level of educational attainment, arthritis and other chronic diseases have been found to be associated with the poverty rate of one's socioeconomic environment. Two studies of arthritis prevalence in Canada examined correlations between geographic and provincial location and rates of self-reported arthritis [27, 30]. One study that adjusted for age, sex, education, and BMI found that Quebec had a lower prevalence of arthritis and most other chronic conditions compared to the remaining provinces in Canada, indicating that place of residence is an important factor for arthritis prevalence [30]. The second Canadian study found both individual- and regional-level SES measures, such as the prevalence of low-income families within a region, to be associated with variations in the rates of self-reported arthritis [27]. Additionally, a study of 7,770 patients in family practice sites throughout North Carolina showed that after adjusting for individual educational attainment, both white and non-Hispanic African American individuals from communities with high poverty rates had higher rates of self-reported arthritis [26]. Further, previous results from the Johnston County Osteoarthritis Project showed that living in a community with a poverty rate of greater than 25% was positively associated with knee radiographic OA and symptomatic OA [15], as well as with disability, in persons with hip OA [17].

Currently, there is very limited research on the association between educational attainment and hip OA, and community poverty level factors have not been examined in radiographically diagnosed hip OA. A better understanding of the role of individual and community attributes could help policymakers develop targeted programs toward reducing hip OA. The purpose of this study was to examine associations between educational attainment and occupation (individual-level SES) as well as neighborhood household poverty rate (community-level SES) with hip radiographic OA and symptomatic OA in the Johnston County Osteoarthritis Project. It is hypothesized that both individual- and community-level SES factors will be independently associated with both hip radiographic OA and symptomatic OA.

Significance & Innovations

  • Osteoarthritis (OA) of the hip is a leading cause of disability in older adults.
  • Few studies have examined how an individual's socioeconomic status affects hip OA outcomes.
  • In our study, we found that education and community poverty were associated with hip OA.
  • Understanding the role of individual and community attributes could help policymakers develop targeted programs toward reducing hip OA.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

The Johnston County Osteoarthritis Project is an ongoing community-based cohort of persons with OA, which is described in detail in a previous publication [32]. Briefly, this study is a prospective cohort study of knee and hip OA. The study was designed to be representative of civilian, noninstitutionalized African Americans and whites ages >45 years who resided in 1 of 6 towns or townships in Johnston County, North Carolina, for at least 1 year, were living in the county at the time of study enrollment, and were physically and mentally capable of completing the study protocol.

This investigation is a cross-sectional analysis examining the frequency of radiographic OA and symptomatic OA and their associations with 2 individual social determinants (education and occupation) and a community contextual factor (block group poverty rate). Analyses were carried out using baseline data from 4,098 individuals who entered the cohort in 2 periods: 1990–1997 (original study enrollment period) and 2003–2004 (cohort enrichment with new enrollees) (Figure 1). All participants completed 2 in-home interviews and a limited clinical and functional examination, which included an assessment of weight (kg) using a balance-beam scale, an assessment of height (cm) measured with a stadiometer, and a radiographic examination of the hips to diagnose radiographic OA and symptomatic OA. Pelvic radiographs were not obtained from women ages <50 years (n = 482). At least 1 hip radiograph was available for 3,384 individuals, who were included in the analyses (Figure 1). At baseline, all participants provided informed written consent at the time of recruitment. The study was approved by the Institutional Review Boards of the University of North Carolina Schools of Medicine and Public Health and the Centers for Disease Control and Prevention.

image

Figure 1. Participant flow chart. § = sample excludes those without radiographic data for at least one hip; OA = osteoarthritis; ‡ = sample excludes those without radiographic data for both hips; ‡ = sample excludes those without radiographic and pain data for at least one hip; sOA = symptomatic OA; † = sample excludes those without radiographic and pain data for both hips.

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OA measures

Four main OA measures were used in this study: radiographic OA and symptomatic OA, defined both generally (OA in either hip) or bilaterally (OA in both hips).

Radiographic hip OA

Women ages ≥50 years and all men had anteroposterior pelvic radiographs that were obtained with the subject supine and with their feet at 15 degrees of rotation. Radiographs of the hips were read by a single bone and joint radiologist (JBR) and assigned a Kellgren/Lawrence (K/L) grade for each hip on a scale of 0–4, where higher values show evidence of more severe osteoarthritic deterioration of the joint. Unilateral radiographic OA was defined as having a K/L grade ≥2 in one hip and bilateral radiographic OA was defined as having a K/L grade ≥2 in both hips.

Symptomatic hip OA

Symptomatic hip OA was defined as the presence of radiographic OA (K/L grade ≥2) in at least one hip, plus self-reported symptoms in the same hip. Hip symptoms for each hip were assessed by answering the question: “On most days, do you have pain, aching, or stiffness in your (right, left) hip?” A general finding of symptomatic OA was made for a person if there was symptomatic OA in at least one hip. Unilateral symptomatic OA was defined as having radiographic OA with symptoms in one hip and bilateral symptomatic OA was indicated by radiographic OA in both hips and symptoms in both hips.

Primary exposures of interest

The primary exposures of interest included 2 individual-level measures of SES and 1 community-level measure of SES.

Individual-level measures of SES

Education was used as a dichotomous variable indicating having completed less than 12 years of formal schooling or 12 years or more (referent).

Occupation was dichotomized to distinguish between occupations that are managerial (referent) and those that are not. Six US Census classifications were applied to the principal occupation indicated by the participant. Occupations classified as nonmanagerial were 1) service; 2) farming, forestry, and fishing; 3) precision production, craft, and repair; and 4) operators, fabricators, and laborers. Managerial occupations were 5) managerial and professional and 6) technical, sales, and administrative support [33].

Community-level measure of SES

Household poverty rate was determined through the percentage of households with income below the poverty level within a US Census block group at the time of entry into the study. Research suggests that the percentage of households in poverty is a good indicator for community-level SES, and has been shown in some studies to be a better indicator of the SES environment than census tract measures [28, 34]. Each participant's physical address was geocoded, linked to the US Census block group identification number, and then used to extract aggregated census information. The census-based household poverty rate assigned to a participant's block group is intended to indicate the contextual or community SES where the resident lives. For example, 2 residents of the same block group will share the same household block group poverty rate, but they may have different individual SES characteristics, such as educational attainment and occupation. In Johnston County, 67 of 68 block groups had at least 1 participant, where household poverty rates range from 0–50%. For this study, poverty was categorized based on tertile cut points of block group poverty rates, resulting in cut points of 12% and 25%. This 3-level variable was defined as low (referent), medium, or high community poverty rates.

Covariates

Factors considered as potential confounders of the associations between SES variables and hip OA measures were sex (male, female), race (African American, white), BMI (weight in kg/height in m2), current smoker (no, yes), self-reported prior hip injury (no, yes), and occupational activity score. Occupational activity score was based on self-reports of frequencies of 4 employment-related activities: squatting, standing, lifting, and walking (where 0 = never, 1 = seldom, 2 = sometimes, 3 = often, and 4 = always). The sum (range 0–16) of the individual scores was dichotomized as low (<10) or high (≥10).

Statistical analysis

For this study, we carried out a complete case analysis, leading to an additional 297 subjects to be excluded from the analysis due to missing values for 1 or more covariates, leaving 3,087 for analysis (Figure 1). The frequency of hip measures and SES variables was similar between data sets, which did and did not exclude subjects for missing values for covariates. All analyses were carried out using the statistical software package SAS, version 9.2.

For the assessment of the associations between hip radiographic OA measures and individual and community SES, odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression models for the presence of hip radiographic OA or hip symptomatic OA [35]. Multinomial logistic models were used to assess the association of predictors with hip radiographic OA laterality measures (e.g., unilateral radiographic OA and bilateral radiographic OA versus no radiographic OA). All models were adjusted for age. Using manual backward elimination, other potential confounders listed above as covariates were removed from models, beginning with those with the highest P values. Variables were retained in the final models if their inclusion changed the estimate of effect by >10% [35]. Adjustment for covariates beyond age did not appreciably alter the estimates of effect by >10% for either hip radiographic OA or hip symptomatic OA; therefore, reported associations are adjusted for age only. Additional analyses managed within-street–level correlation (with an exchangeable working correlation structure) using generalized estimating equations methodology. We found no meaningful differences in results when accounting for within-street correlation; therefore, reported results are from models that do not consider street-level correlation.

Effect measure modification on the multiplicative scale between all SES predictors and race was evaluated using the log-likelihood ratio test to compare logistic regression models with and without the cross-product terms. We found no significant evidence of effect modification by race. Similar analyses also found no effect modification by sex.

To evaluate the possibility of a segregation effect, we also looked at the percentage of African American residents in each block group. For the 67 block groups, the percentage of African American residents ranged from 0–93% and averaged 16.8%. Because of racial disparities in income, there is a strong positive correlation (r = 0.83) between household poverty rate and this measure of segregation. Ultimately, the percentage of African American residents in the block group was determined to have less predictive value and was dropped from the final modeling approach.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

There were 3,087 participants in the Johnston County Osteoarthritis Project who met the study criteria for this analysis, of which 31.8% were African American and 56.8% were women (Table 1). Overall, 27% had radiographic OA, 10.6% had radiographic OA in both hips, 9.7% with radiographic OA reported symptoms in the same hip, and 2.1% had bilateral symptomatic OA. The mean age of the study sample was 62.7 years, 36.1% had less than a high school education, 42.7% had a nonmanagerial job, and 22.2% lived in areas where >25% of the sample lived at or below the poverty level. Demographic characteristics were similar for participants with any (one or both) hip radiographic OA and the subset with bilateral disease. Similarly, those with any (one or both) hip symptomatic OA and the subset with bilateral symptomatic OA were similar with respect to most demographic characteristics, although those with bilateral symptomatic OA had a higher frequency of both obesity and current smokers. The frequency of hip OA measures did not vary according to race, and there was no evidence for effect modification by race on the SES variables (data not shown).

Table 1. Participant characteristics by hip OA subtypea
 All subjects (n = 3,087)Any hip rOA (n = 835)Bilateral hip rOA (n = 327)Symptomatic hip rOA (n = 298)Bilateral symptomatic hip rOA (n = 65)
  1. a

    Values are the percentage unless otherwise indicated. OA = osteoarthritis; rOA = radiographic OA; BMI = body mass index; SES = socioeconomic status.

Demographic characteristics     
Age, mean ± SD years62.7 ± 9.8665.2 ± 10.366.8 ± 10.265.9 ± 9.9564.9 ± 9.52
Women56.857.159.060.150.8
African American race31.832.133.331.233.8
BMI, mean ± SD kg/m229.2 ± 5.9528.9 ± 5.929.3 ± 6.229.9 ± 6.329.8 ± 6.3
Obesity38.438.441.946.352.3
Current smoker20.618.417.120.824.6
Hip injury6.26.97.011.79.2
High occupational activity46.647.744.347.749.2
SES characteristics     
<12 years of education36.142.347.749.053.8
Nonmanagerial occupation42.741.037.937.933.8
Poverty, mean ± SD19.6 ± 10.320.2 ± 10.320.5 ± 10.420.5 ± 10.319.8 ± 11.0
Block group poverty     
Low (<12%)21.519.918.318.823.1
Medium (12–25%)56.352.849.854.453.8
High (>25%)22.227.331.826.823.1

ORs for the association between individual SES predictors and hip OA measures are shown in Table 2. High community poverty was associated with both hip radiographic OA and symptomatic OA measures in either hip, and low educational attainment was associated with hip symptomatic OA in one or both hips. However, nonmanagerial occupation showed no association with any of the hip OA measures. These associations held for most comparisons, even with simultaneous adjustment for all SES characteristics in the same model. Participants living in areas with poverty levels >25% were more likely to have radiographic OA in one or both hips (OR 1.50, 95% CI 1.18–1.92) when compared to living in areas with poverty levels <12%. Similarly, those who did not attain a high school diploma had 40% greater odds of having symptomatic OA in one or both hips (OR 1.44, 95% CI 1.09–1.91) when compared to those with a high school diploma or more education.

Table 2. Age-adjusted odds ratios and 95% confidence intervals for the association between individual SES variables and hip OA outcomesa
SES characteristicsAny hip rOAbAny hip rOAcSymptomatic hip rOAbSymptomatic hip rOAc
  1. a

    SES = socioeconomic status; OA = osteoarthritis; rOA = radiographic OA.

  2. b

    SES predictors considered separately in individual logistic regression models for each hip OA measure.

  3. c

    SES predictors considered together in the same logistic regression model for each hip OA outcome.

Education    
≥12 years1.001.001.001.00
<12 years1.17 (0.98–1.39)1.13 (0.93–1.36)1.50 (1.16–1.94)1.44 (1.09–1.91)
Occupation    
Managerial1.001.001.001.00
Nonmanagerial1.10 (0.93–1.29)0.99 (0.83–1.19)1.24 (0.97–1.58)1.03 (0.79–1.36)
Block group poverty rate    
<12%1.001.001.001.00
12–25%1.02 (0.83–1.26)1.01 (0.82–1.25)1.14 (0.83–1.57)1.10 (0.80–1.52)
>25%1.53 (1.20–1.94)1.50 (1.18–1.92)1.47 (1.02–2.11)1.37 (0.95–1.98)

The results of age-adjusted multinomial regression models for the association of individual SES characteristics with unilateral and bilateral hip radiographic OA and symptomatic OA are shown in Table 3. When evaluating hip radiographic OA in one or both hips, we observed that persons with <12 years of education were more likely to have bilateral, but not unilateral, hip radiographic OA when compared to those with ≥12 years of education (OR 1.32, 95% CI 1.03–1.70). Similarly, those who lived in areas with a block group poverty rate >25% were observed to have greater odds of bilateral hip radiographic OA (OR 1.96, 95% CI 1.38–2.77). When analyses were limited to only those with symptomatic OA, we observed that those with <12 years of education had greater odds of having both unilateral (OR 1.37, 95% CI 1.02–1.82) and bilateral (OR 2.01, 95% CI 1.19–3.39) hip symptomatic OA when compared to those with ≥12 years of education. Those living in areas with a block group poverty rate >25% were more likely to have unilateral symptomatic OA (OR 1.57, 95% CI 1.04–2.38).

Table 3. Age-adjusted odds ratios and 95% confidence intervals for the association between individual SES variables and hip OA lateralitya
SES characteristicsAny hip rOASymptomatic hip rOA
Unilateral vs. noneBilateral vs. noneUnilateral vs. noneBilateral vs. none
  1. a

    Socioeconomic status (SES) predictors considered separately in individual logistic regression models for each hip osteoarthritis (OA) measure. rOA = radiographic OA.

Education    
≥12 years1.001.001.001.00
<12 years1.10 (0.89–1.36)1.32 (1.03–1.70)1.37 (1.02–1.82)2.01 (1.19–3.39)
Occupation    
Managerial1.001.001.001.00
Nonmanagerial1.02 (0.84–1.24)1.25 (0.98–1.59)1.16 (0.87–1.53)1.48 (0.88–2.49)
Block group poverty rate    
<12%1.001.001.001.00
12–25%0.97 (0.76–1.25)1.05 (0.76–1.44)1.22 (0.84–1.77)0.92 (0.50–1.69)
>25%1.27 (0.95–1.70)1.96 (1.38–2.77)1.57 (1.04–2.38)1.02 (0.50–2.11)

The associations for the evaluation of unilateral or bilateral radiographic OA were attenuated somewhat when considering all SES characteristics simultaneously in regression models (Table 4). In models that included education, occupation, and block group poverty, associations that remained were living in a high poverty block group for bilateral hip radiographic OA (OR 1.87, 95% CI 1.32–2.66) and low education for bilateral disease in the subset restricted to symptomatic OA (OR 1.91, 95% CI 1.08–3.39).

Table 4. Age-adjusted odds ratios and 95% confidence intervals for the association of 3 SES variables simultaneously and hip OA lateralitya
SES characteristicsAny hip rOASymptomatic hip rOA
Unilateral vs. noneBilateral vs. noneUnilateral vs. noneBilateral vs. none
  1. a

    Socioeconomic status (SES) predictors considered together in the same logistic regression model for each hip osteoarthritis (OA) outcome. rOA = radiographic OA.

Education    
≥12 years1.001.001.001.00
<12 years1.11 (0.88–1.40)1.23 (0.93–1.61)1.32 (0.96–1.82)1.91 (1.08–3.39)
Occupation    
Managerial1.001.001.001.00
Nonmanagerial0.95 (0.76–1.18)1.05 (0.80–1.38)0.99 (0.73–1.35)1.16 (0.65–2.06)
Block group poverty rate    
<12%1.001.001.001.00
12–25%0.97 (0.75–1.24)1.02 (0.75–1.41)1.19 (0.82–1.72)0.86 (0.46–1.59)
>25%1.26 (0.94–1.70)1.87 (1.32–2.66)1.50 (0.99–2.29)0.89 (0.43–1.86)

The addition of sex, race, obesity, smoking, hip injury, and occupational activity to regression models did not appreciably alter the results and therefore are not reported here.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

Our results suggest that socioeconomic factors have a significant impact on hip OA measures. Persons living in high poverty areas have a significantly increased association with any radiographic OA (in one or both hips), and those with low educational attainment have a significantly increased association with symptomatic OA. These results were independent of age, sex, race, BMI, smoking, hip injury, occupational physical demands, and other SES factors. Our study supports findings from the few studies that have examined the association of educational attainment with hip OA, and ours is the first study to examine the roles of both community-level and individual-level SES measures in persons with hip OA. Given the high frequency of radiographic OA and symptomatic OA in our rural population [32], it is important to investigate if both individual- and community-level SES contribute to OA measures.

We found that living in a high poverty block group where more than 25% of households had income below the poverty level was associated with radiographic OA overall, an association that was especially strong for those with bilateral disease. The socioeconomic context of a community affects the environment that one lives in regardless of personal socioeconomic characteristics. Community poverty is often characterized by reduced access to health care, recreation facilities, and senior centers. This may contribute to individual risk factors and behaviors associated with hip OA, such as low levels of physical activity and high levels of obesity. However, these individual behaviors do not explain all of the variance seen across the regions. These community socioeconomic characteristics have also been shown to impact health outcomes, including self-rated health, quality of life, chronic conditions, and mortality [29, 36-38].

Our findings with regard to individual SES factors, particularly education, indicate associations with hip OA measures. We found that low education was associated with increased symptomatic OA, reinforcing findings from NHANES-I that also found education to be associated with hip OA [19]. Our results also corroborate results from a Norwegian study that found increased self-reported hip OA among those with fewer than 12 years of education [22], as well as those from a recent study in Denmark that investigated the association between education levels and risk of OA hospitalization among men and women ages 15–73 years [39]. This study reported education to have a modest inverse association with hip OA among both men and women. Of note is a recent Australian study that showed that living in a higher disadvantaged area was associated with fewer hip replacements than living in an area that was less disadvantaged [40]. That study did not report rates of hip OA by region or poverty rates, making it difficult to compare our results.

Our study showed no independent association between managerial or nonmanagerial occupation with any hip OA measure. These results suggest that education and community poverty are more important SES predictors of hip OA measures than occupation. This finding is supported by a previous study that showed that only income and education remained significant predictors of physical health in persons with self-reported arthritis [37]. It has been suggested that community-level SES measures may provide further information that is not captured by individual-level measures alone [29].

OA of the hip is a common disorder and is a leading cause of disability in the elderly. Traditional risk factors for hip OA are age, BMI, genetic predisposition, and occupations that require prolonged periods of standing, bending, or heavy lifting [41, 42]. However, these individual-level risk factors do not account for all of the associations observed; therefore, it has been argued that SES is a fundamental cause of disease that puts people “at risk of risks” [43]. SES is a complex combination of an individual's education, income, and occupation and the socioeconomic environment of one's neighborhood. These various measures of SES may operate through different mechanisms to affect the risk for OA, including the potential for SES to influence lifestyle behaviors, preventive health care, health management, problem solving abilities, and access to health care. For example, those with higher income have better access to medical care; it has also been suggested that individuals with higher education are better able to process information regarding healthy behaviors [23].

Strengths of our study include the utilization of measures of both radiographic and symptomatic hip OA in a well-described sample of men and women with a high participation rate that includes a large representation of African American participants. The Johnston County Osteoarthritis Project enabled us to obtain data from a large sample, and we were able to obtain data from virtually all block groups within Johnston County (67 of 68). Finally, we were able to examine segregation as well as household poverty rate as a contextual variable.

There are also limitations that warrant mention. The study data are limited to individuals living within a single, nonurban county, thereby limiting generalizability. Further, we did not include a measure of participant income as an individual SES measure, since these data were not available. Because household poverty rates were documented by block group, our community SES measure was fairly crude, since they were limited to US Census variables that focused on aggregated individual-level variables. Since street of residence represents diversity among its members, our primary analysis does not account for correlation between those living on the same street. However, additional models that do account for such a correlation were considered. Results remained robust with the exception of the effect for block group poverty levels exceeding 25%, which exhibited slightly attenuated effects and wider CIs relative to the reported results. However, the results from this additional consideration did not change statistically significant results or the general nature of our conclusions. The SES measures used in our study may represent different facets of social circumstances; however, all individual measures can affect one's health behaviors and predict health status [44, 45]. Area-level poverty has been shown to be a good measure of geographic distribution of socioeconomic inequalities in health, and enables measurement of the effect of local environment beyond the impact of individual SES [46]. There is also the issue of reverse causation, where having OA could affect SES. Of the SES measures used in our study, education is the least likely to be affected by reverse causation, since it generally occurs early in life and OA is generally a disease of aging. Finally, our study is based on cross-sectional data; therefore, we are not able to determine causality.

In some previous studies it has been suggested that race is a proxy for SES. However, in our study we found that frequency of radiographic OA and symptomatic OA was similar in whites and African Americans despite African Americans being more likely to be obese, have more physically demanding occupations, have lower education, and live in higher-poverty areas. It has also been shown that pain and function, as well as pain perception, are not different between African Americans and whites at any radiographic severity level of OA [47, 48]. That the frequency, function, and pain of hip OA are similar in whites and African Americans supports our findings that socioeconomic factors are more important determinants of radiographic OA and symptomatic OA measures than race.

In conclusion, our study expands the literature examining the association between measures of SES and OA measures. We were able to examine SES measures in association with hip radiographic OA, which is an understudied area of OA research. Further, we were able to identify the relationship between SES and several different hip OA measures, including radiographic and symptomatic hip OA, as well as unilateral and bilateral hip OA measures for both radiographic OA and symptomatic OA. We were also able to examine these associations in a large sample of both African Americans and whites. Finally, our study examined not only 2 important measures of individual SES (education and occupation), but also included a measure of community SES (block group poverty rate) to help identify aspects of SES that are important predictors of hip OA measures.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Callahan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Prizer, Randolph, Jordan, Callahan.

Acquisition of data. Schoster, Renner, Jordan.

Analysis and interpretation of data. Cleveland, Schwartz, Callahan.

ACKNOWLEDGMENTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES

The authors thank My-Linh Luong for assistance in manuscript preparation, the staff of the Johnston County Osteoarthritis Project for their longstanding and dedicated work, as well as the Project participants, without whose continuing cooperation none of this work would be possible.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. ACKNOWLEDGMENTS
  9. REFERENCES
  • 1
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