To determine the risk of cardiovascular disease (CVD) among osteoarthritis (OA) patients using population-based administrative data from British Columbia, Canada.
To determine the risk of cardiovascular disease (CVD) among osteoarthritis (OA) patients using population-based administrative data from British Columbia, Canada.
The medical history of a random sample of 600,000 individuals from 1991–2009 was analyzed. A total of 12,745 OA cases and up to 3 non-OA individuals matched by age, sex, and year of diagnosis were followed for CVD events. Cox proportional hazards and Poisson regression models were used to estimate the relative risks (RRs) of CVD, myocardial infarction, ischemic heart disease (IHD), congestive heart failure (CHF), and stroke after adjusting for available sociodemographic and medical factors.
OA was an independent predictor of CVD. The adjusted RRs were 1.15 (95% confidence interval [95% CI] 1.04–1.27), 1.26 (95% CI 1.13–1.42), and 1.17 (95% CI 1.07–1.26) among older men, younger women, and older women, respectively. Analyses were stratified by age and sex due to statistically significant interactions between OA and age and sex. RRs among older men, younger women, and older women were 1.33 (95% CI 1.11–1.62), 1.66 (95% CI 1.37–2.01), and 1.45 (95% CI 1.22–1.72) for IHD, respectively, and 1.25 (95% CI 1.02–1.54), 1.29 (95% CI 1.00–1.68), and 1.20 (95% CI 1.03–1.39) for CHF, respectively. Compared to non-OA individuals, OA cases who underwent total joint replacements had a 26% increased risk of CVD.
This prospective longitudinal study suggests that OA is associated with an increased risk of CVD. Older men and adult women with OA had a higher risk of CVD, particularly IHD and CHF. Further studies are needed to confirm these results and to elucidate the potential biologic mechanisms.
Cardiovascular disease (CVD), such as myocardial infarction (MI), ischemic heart disease (IHD), congestive heart failure (CHF), and stroke, are major causes of morbidity and mortality worldwide ([1, 2]). Coronary heart disease and related risk factors are the leading causes of morbidity and mortality in Canada ([3, 4]). Established risk factors for CVD include demographic, clinical, social, and behavioral factors, such as age, sex, obesity, hypertension, cholesterol, income, ethnicity, exercise, smoking, and diet ([1-3, 5]). Recently, it has become clear that systemic inflammation can promote CVD ([6, 7]). Rheumatic diseases such as rheumatoid arthritis, psoriatic arthritis, and systematic lupus erythematosus are a heterogeneous group of disorders that are characterized by acute or chronic inflammation. These rheumatic diseases have been linked to an increased risk of CVD (). Frailty and muscle weakness were also observed as risk factors and comorbidities among individuals with CVD (). Studies have shown that the increased risk of CVDs and mortality is caused in part by physical inactivity ([10, 11]). Recent studies have also shown that immobility resulting from arthritis may increase CVD risk among elderly patients and therefore shorten one's lifespan ().
Osteoarthritis (OA) in the large weight-bearing joints, such as the hip and knee, is the most common type of arthritis and is a leading cause of disability ([13-15]). Globally, approximately 10–12% of the population have OA ([16-19]). OA is associated with older age, female sex, obesity, joint injury, occupation, and high levels of physical activity ([13, 16, 19, 20]). Although OA is the most common rheumatic disease, very little is known about the link between OA and CVD. A number of factors suggest that OA may be associated with an increased risk of CVD. Although OA is often referred to as a degenerative disease, synovial inflammation plays a role in the development of the early stage of OA (). Furthermore, muscle weakness is a frequent symptom observed among individuals with OA (). In an observational study, Slemenda et al linked muscle weakness to narrowed joint space, increased knee pain, and elevated development of OA in elderly women (). With OA progression, severe pain in the joints makes patients less physically active compared to individuals without arthritis (). In addition, nonsteroidal antiinflammatory drugs (NSAIDs), which are commonly used to treat OA-related pain, are associated with an increased risk of CVD ([25, 26]).
In summary, the reasons to suggest that individuals with OA may experience excess CVD events include reduced physical activity, chronic inflammation, muscle weakness, and use of NSAIDs. The relationship between OA and CVD has not been studied extensively in prospective longitudinal studies. However, increased odds ratios of CVD among OA cases were observed in the studies by Ong et al (), Kadam et al (), and Rahman et al (). Studies have also shown that compared with the general population, patients with OA have increased mortality that is caused by CVD, diabetes mellitus, dementia, and cancer ([30, 31]). Since OA may increase the risk of CVD through several mechanisms, we aimed to determine whether OA increases the risk for hospitalized CVD in a longitudinal study. We also examined the risks of MI, IHD, CHF, and stroke separately for men and women with OA. Considering that OA is a common condition among elderly people, a better understanding of the relationship between OA and CVD could help to extend future management strategies beyond the current focus on treating chronic symptoms and surgery for advanced OA.
We used a large, random, and representative sample of all individuals registered in the Medical Services Plan as residents of British Columbia (BC) from April 1991 to March 2009. The sample was selected from an administrative database maintained by the BC Ministry of Health. Our sample included individual-level information on date of birth, sex, billing information for any health consultation, socioeconomic status (SES) by area of residence, hospital diagnoses, dates of hospital admissions, and date and cause of death for 600,000 randomly selected residents of BC. Vital statistics and death data were linked at the individual level using personal health numbers. Personal health numbers assigned to each resident of BC were replaced by serial numbers to preserve anonymity. These serial numbers were used to track all records at the individual level and to check individuals' first hospital CVD diagnoses during the study period. These records do not include data for hospital outpatients or patients treated at emergency health care units. This study was approved by the Research Ethics Committee at the University of British Columbia, Canada.
The exposure variable was the OA diagnosis by a health professional using International Classification of Diseases, Ninth Revision (ICD-9) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes. Patients with OA were identified using the case definition of at least 2 visits to a health professional in 2 years separated by at least 1 day or 1 discharge from the hospital with an ICD-9 code of 715 or an ICD-10 code from M15–M19. A visit was defined as any service with the exclusion of diagnostic procedures and certain other procedures, such as dialysis/transfusion, anesthesia, obstetrics, or therapeutic radiation. Visits to all types of health professionals were included, and the date of diagnosis was coded as the date of the second health professional visit or the date of discharge from the hospital. Individuals with a history of CVD prior to their OA diagnosis, based on a physician's consultation or hospital admission, were excluded. All existing OA subjects ages ≥20 years in the random sample who met the above case definition from 1991 to 1996 were identified as the exposed group after deleting prevalent CVD cases.
In the Canadian health care system, a referral from the family physician is necessary to see a specialist, such as an orthopedic surgeon. Therefore, individuals with advanced OA usually get a referral to an orthopedic surgeon for their surgical consultation. To examine the relationship between OA severity and the risk of CVD, all exposed cases were divided into 3 groups according to disease severity: 1) OA diagnosis only, 2) at least 1 orthopedic surgeon consultation, or 3) at least 1 total joint replacement (TJR) or revision before the baseline (March 1996). Orthopedic surgeon consultations were identified by looking at the physician specialty code in the physician's billing data as well as in the hospital records. TJR cases were identified from hospital records using procedure codes (Canadian Classification of Diagnostic, Therapeutic, and Surgical Procedures) for hip TJR and revision (935.x, 936.5, 936.6, 936.7, and 936.8) and for knee TJR and revision (934.0 and 934.1). These codes have been explained in detail previously ().
From the random sample, up to 3 non-OA individuals were matched for each OA patient based on exact age, sex, and year of OA diagnosis (the index date). Individuals in the non-OA comparison group never had a diagnosis for OA from 1991 to 2009. Similar to the exposed group, the comparison group was age ≥20 years and did not have CVD diagnoses prior to the index date.
Hospital admission for CVD was the primary outcome in this study. Specific CVD events such as MI, IHD other than MI, CHF, and stroke were considered as secondary outcomes. All primary and secondary CVD events were identified from the hospital discharge records based on ICD-9 codes 410–414, 428, 430–434, 436, and 438. The corresponding ICD-10 codes are I20–I25, I50, and I60–I64. Detailed classifications of these codes according to IHD, MI, CHF, and stroke are shown in Table 1.
|Disease||ICD-9 code||ICD-10 code|
|Ischemic heart disease||410–414||I20–I25|
|Acute myocardial infarction||410||I21|
|Other acute forms of CHD||411||I24|
|Old myocardial infarction||412||I22–I23|
|Other forms of chronic CHD||414||I25|
|Congestive heart failure||428||I50|
|Stroke||430–434, 436, 438||I60–I64|
Common risk factors for CVD include age, sex, family history, high cholesterol, high blood pressure, diabetes mellitus, high body mass index (BMI), smoking, and diet ([1, 5]). Other than the matched variables age and sex, the individual-level variables that were available in the database and adjusted for in the analysis included neighborhood SES and health conditions known to increase risk. SES was assigned based on residential address linked to census data at the level of enumeration area (≥1 adjacent blocks, up to 650 dwellings) and was grouped into 5 income groups (range 1–5, where 1 = lowest and 5 = highest) based on mean household income of those residents' data (). Individuals' history of diabetes mellitus, hypertension, hyperlipidemia, and chronic obstructive pulmonary disease (COPD) was assessed on or before the index date. These conditions were defined by visits to health care professionals or hospital admissions with ICD-9 codes as follows: 1) type 2 diabetes mellitus (code 250), 2) hypertension (code 401), 3) hyperlipidemia (code 272), and 4) COPD (codes 490, 491, 494, and 496). Charlson comorbidity scores ([34, 35]) for all subjects in the study were also calculated on or before the index date. The Charlson score contains 19 comorbidity categories, and a total score for each patient was calculated by adding the weights for each condition.
BMI was not measured in the administrative data; therefore, we imputed BMI categories using data from the Canadian Community Health Survey (CCHS) cycles 1.1, 2.1, and 3.1. The CCHS is a large, cross-sectional survey representative of the Canadian population carried out by Statistics Canada. This survey contains nationally representative data on health determinants, health status, and health services utilization. A detailed description of the survey design, sample, and interviewing procedures may be found elsewhere (). The method of imputation was designed to reproduce in our administrative data set the associations of BMI with both OA and CVD, observed in the CCHS. Individuals with OA were identified using self-reported OA and up to 3 non-OA individuals were randomly matched to each OA subject according to age, sex, and survey cycle. We used the CCHS question about heart disease as a proxy variable for CVD because not all components of CVD were measured in the first 3 cycles. All OA and non-OA individuals were grouped according to OA status, heart disease status (yes/no), sex, and 10-year age groups. For each group, we calculated the proportion of individuals in each of the 4 BMI categories: underweight (<18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), and obese (≥30.0 kg/m2). Finally, we imputed the same proportion of individuals in each of the BMI categories from the CCHS data into our administrative data by matching on OA status, CVD status, sex, and age.
The followup period for analysis started on the date when individuals met the case definition for OA (index date) and continued until hospitalization for CVD, death, emigration, or the end of the study period (March 31, 2009), whichever came first. Person-years of risk were calculated for the entire followup period. The relative risks (RRs) and 95% confidence intervals (95% CIs) were evaluated using the Cox proportional hazards models. The proportionality assumptions for proportional hazards models were assessed by observing the Kaplan-Meier curves of the survival function versus the survival time, and the graph of the log [− log (survival function)] versus log of survival time. In addition, the proportionality tests were performed in the multivariable models and the P values were reported. The RRs were estimated by fitting Poisson regression models where proportionality test P values were significant. SAS, version 9.3 was used throughout the study to perform the analyses.
Between April 1991 and March 1996, we documented 12,745 existing OA patients in the random sample and selected 36,886 non-OA individuals matched by age, sex, and index date. The baseline characteristics of the study subjects according to exposure status are shown in Table 2. The mean age of the OA patients was 58.2 years and 60% were women. At baseline, 11% of OA cases had COPD, 20% were hypertensive, and 5% cases had diabetes mellitus. These baseline characteristics were significantly more common in the exposed group than in the non-exposed group (P < 0.01). With 13 years of mean followup corresponding to 650,324 person-years, we observed 7,995 new hospitalized CVD cases. Of those, 2,023 were MI, 2,335 were IHD other than MI, 1,720 were CHF, and 1,917 were stroke cases. This gives an incidence rate for overall CVD of 12.3 (95% CI 12.27–12.33) per 1,000 person years.
|Exposed (OA)||Nonexposed (non-OA)|
|Age, mean ± SD years||58.2 ± 14.5||57.5 ± 14.3|
|Body mass index, kg/m2|
|Charlson score, mean ± SD||0.41 ± 0.92||0.35 ± 0.98|
In the multivariable Cox proportional hazards model, statistically significant interactions were observed between OA and age and between OA and sex (P < 0.01). Separate analyses were performed using 4 strata: men ages <65 years, men ages ≥65 years, women ages <65 years, and women ages ≥65 years. We refer to these 4 groups as younger men, older men, younger women, and older women, respectively. None of the other variables showed statistically significant interactions with the exposure variable. The RRs and 95% CIs of CVD from the unadjusted models and from the multivariable models according to the subgroups are shown in Table 3. The proportionality test P values were 0.41, 0.002, 0.13, 0.67, and 0.006 among younger men, older men, younger women, older women, and the total subjects, respectively. The RRs were estimated using Poisson regression models for older men and for total subjects. All of the covariates were significant in at least 1 of the 4 age–sex strata; therefore, we have included all variables in the multivariable models. In the crude analyses, individuals with OA showed a statistically significantly increased risk of CVD in all 4 age–sex strata. In the multivariable models adjusted for history of diabetes mellitus, hypertension, hyperlipidemia, COPD, Charlson score, BMI, and SES, OA was an independent predictor of CVD for older men (RR 1.15, 95% CI 1.04–1.27), younger women (RR 1.26, 95% CI 1.13–1.42), and older women (RR 1.17, 95% CI 1.07–1.26), but not for younger men (RR 1.08, 95% CI 0.97–1.19). Hypertension, diabetes mellitus, higher Charlson comorbidity score, imputed BMI, and lower SES were associated with an increased risk of CVD.
|Variables||Total, RR (95% CI)||Men, RR (95% CI)||Women, RR (95% CI)|
|Age <65 years||Age ≥65 years||Age <65 years||Age ≥65 years|
|Exposure to OA|
|Unadjusted||1.23 (1.17–1.29)||1.19 (1.08–1.32)||1.21 (1.10–1.33)||1.51 (1.35–1.69)||1.23 (1.14–1.33)|
|Adjusted||1.13 (1.07–1.18)||1.08 (0.97–1.19)||1.15 (1.04–1.27)||1.26 (1.13–1.42)||1.17 (1.07–1.26)|
|Body mass index, kg/m2|
|<18.5||1.29 (1.11–1.50)||1.04 (0.55–1.94)||1.56 (1.07–2.28)||0.95 (0.64–1.40)||1.45 (1.20–1.74)|
|25.0–29.9||1.09 (1.03–1.15)||1.33 (1.18–1.49)||1.02 (0.92–1.13)||1.26 (1.11–1.44)||0.99 (0.90–1.08)|
|≥30.0||1.40 (1.33–1.48)||1.93 (1.70–2.18)||1.14 (1.01–1.28)||1.88 (1.65–2.14)||1.17 (1.07–1.29)|
|1 (low)||1.07 (0.99–1.14)||1.09 (0.94–1.26)||1.00 (0.86–1.15)||1.20 (1.01–1.43)||1.10 (0.98–1.23)|
|2||1.03 (0.96–1.10)||1.00 (0.87–1.14)||1.06 (0.92–1.22)||1.19 (1.01–1.41)||0.97 (0.86–1.09)|
|3||1.05 (0.98–1.12)||0.97 (0.85–1.12)||1.08 (0.94–1.24)||1.14 (0.96–1.35)||1.05 (0.93–1.18)|
|4||1.05 (0.99–1.13)||0.87 (0.77–1.00)||1.04 (0.91–1.19)||1.29 (1.10–1.51)||1.04 (0.93–1.17)|
|COPD||1.17 (1.08–1.26)||1.23 (1.03–1.46)||1.06 (0.92–1.24)||1.31 (1.10–1.57)||1.08 (0.94–1.24)|
|Hypertension||1.43 (1.36–1.50)||1.93 (1.72–2.17)||1.32 (1.20–1.46)||2.23 (1.97–2.53)||1.49 (1.38–1.61)|
|Hyperlipidemia||1.02 (0.93–1.13)||1.26 (1.06–1.51)||0.98 (0.80–1.21)||1.27 (1.03–1.56)||0.79 (0.67–0.94)|
|Diabetes mellitus||1.73 (1.60–1.88)||2.05 (1.70–1.22)||1.50 (1.29–1.74)||2.30 (1.89–2.80)||1.79 (1.56–2.05)|
|Charlson score||1.05 (1.02–1.07)||1.15 (1.07–1.22)||1.06 (1.01–1.10)||1.14 (1.06–1.21)||1.07 (1.03–1.10)|
The effects of OA on specific CVD events such as MI, IHD other than MI, CHF, and stroke are shown in Table 4. OA showed statistically significant RRs for IHD, CHF, MI, and stroke in the unadjusted analyses. In the adjusted model, OA showed statistically significant RRs for incident IHD in all age–sex strata except younger men. Adjusted RRs for IHD were 1.33 (95% CI 1.11–1.62), 1.66 (95% CI 1.37–2.01), and 1.45 (95% CI 1.22–1.72) for OA in older men, younger women, and older women, respectively. RRs for CHF were 1.29 (95% CI 1.00–1.68), 1.25 (95% CI 1.02–1.54), and 1.20 (95% CI 1.03–1.39) for OA among younger women, older men, and older women, respectively. MI and stroke did not show any statistically significant association with OA in the multivariable analyses.
|Outcome||Total, RR (95% CI)||Men, RR (95% CI)||Women, RR (95% CI)|
|Age <65 years||Age ≥65 years||Age <65 years||Age ≥65 years|
|Unadjusted||1.49 (1.37–1.63)||1.17 (1.00–1.37)||1.41 (1.17–1.69)||1.94 (1.61–2.34)||1.54 (1.31–1.82)|
|Adjusted||1.30 (1.19–1.42)||1.07 (0.91–1.25)||1.33 (1.11–1.62)||1.66 (1.37–2.01)||1.45 (1.22–1.72)|
|Unadjusted||1.43 (1.29–1.58)||1.47 (1.07–2.01)||1.28 (1.05–1.56)||1.56 (1.20–2.03)||1.25 (1.08–1.43)|
|Adjusted||1.15 (1.04–1.28)||1.35 (0.98–1.86)||1.25 (1.02–1.54)||1.29 (1.00–1.68)||1.20 (1.03–1.39)|
|Unadjusted||1.20 (1.09–1.32)||1.19 (0.99–1.42)||1.12 (0.92–1.36)||1.17 (0.93–1.48)||1.14 (0.97–1.35)|
|Adjusted||1.02 (0.92–1.12)||1.06 (0.88–1.28)||1.11 (0.91–1.36)||0.95 (0.75–1.21)||1.06 (0.89–1.26)|
|Unadjusted||1.15 (1.04–1.27)||1.10 (0.86–1.40)||0.95 (0.78–1.17)||1.34 (1.06–1.69)||1.07 (0.92–1.24)|
|Adjusted||0.96 (0.87–1.06)||0.99 (0.77–1.26)||0.96 (0.78–1.17)||1.13 (0.89–1.44)||1.02 (0.87–1.19)|
Among OA cases, 966 (8%) had at least 1 TJR or revision and 2,071 (16%) had visits to orthopedic surgeons before baseline. To determine whether a dose-response relationship with OA severity exists, we ran multivariable proportional hazards and Poisson regression models using OA diagnosis, visits to an orthopedic surgeon, and TJR as exposures (Table 5). The TJR group showed higher RRs than the OA diagnosis and orthopedic surgeon consultation groups for overall CVD, IHD, and CHF. RRs were 1.26 (95% CI 1.12–1.41), 1.44 (95% CI 1.16–1.79), and 1.46 (95% CI 1.16–1.83) for overall CVD, IHD, and CHF, respectively, in the TJR group. Men who had a TJR had RRs of 1.17 (95% CI 0.97–1.40), 1.22 (95% CI 0.89–1.67), and 1.80 (95% CI 1.26–2.58) for CVD, IHD, and CHF, respectively. Women who had a TJR had RRs of 1.31 (95% CI 1.12–1.54), 1.73 (95% CI 1.28–2.35), and 1.36 (95% CI 1.02–1.81) for CVD, IHD, and CHF, respectively. The orthopedic surgeon consultation group showed an increased risk of IHD among women (RR 1.45, 95% CI 1.11–1.90). However, the OA diagnosis group showed significantly higher RRs for CVD and IHD among both men and women.
|Exposure||Total, RR (95% CI)||Men, RR (95% CI)||Women, RR (95% CI)|
|OA diagnosis||1.11 (1.05–1.17)||1.11 (1.02–1.20)||1.13 (1.05–1.22)|
|OS consultation||1.10 (0.93–1.22)||1.06 (0.91–1.23)||1.14 (0.98–1.31)|
|TJR||1.26 (1.12–1.41)||1.17 (0.97–1.40)||1.31 (1.12–1.54)|
|OA diagnosis||1.30 (1.18–1.43)||1.16 (1.01–1.33)||1.47 (1.28–1.69)|
|OS consultation||1.25 (1.04–1.49)||1.10 (0.86–1.41)||1.45 (1.11–1.90)|
|TJR||1.44 (1.16–1.79)||1.22 (0.89–1.67)||1.73 (1.28–2.35)|
|OA diagnosis||1.09 (0.97–1.23)||1.15 (0.94–1.41)||1.08 (0.93–1.24)|
|OS consultation||1.19 (0.96–1.48)||1.40 (1.00–1.95)||1.10 (0.82–1.46)|
|TJR||1.46 (1.16–1.83)||1.80 (1.26–2.58)||1.36 (1.02–1.81)|
To our knowledge, this is the first longitudinal study of the relationship between OA and incident CVD using an administrative database. In this population-based study with up to 18 years of followup, we observed that OA increased the risk of hospitalized CVD in both younger and older women and in older men, compared with their non-OA counterparts. The estimated increased risk of CVD was 23% among younger women, 17% among older women, and 15% among older men. Younger women with OA had a 66% increased risk of IHD and a 29% increased risk of CHF. For older women and men with OA, the risks of IHD other than MI and CHF were relatively lower, but were statistically significant. We also observed that women who underwent TJR had a 31% increased risk of CVD, a 73% increased risk of IHD, and a 36% increased risk of CHF, and men who underwent TJR had an 80% increased risk of CHF. In our study, individuals with OA did not show a significant association with MI or stroke.
Evidence shows that patients with OA have higher CVD rates compared to non-OA individuals. Kadam et al () observed 73%, 36%, and 28% higher odds for IHD, angina, and CHF, respectively, among OA cases compared to non- OA controls. In a cross-sectional study, Ong et al () observed significantly higher odds for self-reported CVD, coronary heart disease, and angina among OA cases. Recently, Rahman et al () observed statistically significant associations between OA and prevalent CVD. In addition, stroke was not associated with OA in the studies by Rahman et al () and Ong et al (). Our prospective study results are consistent with these findings.
Although the primary focus of this research was to determine the risks of CVD among physician-diagnosed OA cases, some previous studies had provided evidence that mortality due to CVD was increased in individuals with OA ([30, 31]). In a cohort study, Nüesch et al () estimated that the patients with OA had excess all-cause mortality compared with the general population, and the standard mortality ratio for CVD was 1.71 (95% CI 1.49–1.98). Hochberg () reviewed the literature on OA and mortality and found that several studies reported an increased risk of death among individuals with OA ([37-42]). However, these studies were relatively small, and not all relevant factors were adjusted for in the multivariable analyses.
We analyzed a representative sample from a prospectively collected administrative database from April 1991 to March 2009. By selecting OA patients from 1991 to 1996, we ensured that both the exposed and nonexposed groups had sufficient time to develop the outcomes of interest. Inclusion of incident CVD cases as events protected the results from potential reverse causality bias. Studies have shown that the hospital discharge database has high validity ([43-45]), especially for cardiovascular disorders such as heart failure and IHD, for which approximately 90% of diagnoses have been demonstrated to be correct, with the positive predictive values generally between 75% and 90% (). The results were adjusted for age, sex, SES, BMI, and several conditions known to be associated with CVD, such as COPD, hypertension, hyperlipidemia, diabetes mellitus, and a number of severe conditions that were included in the Charlson comorbidity index. Finally, we were able to perform separate analyses for specific CVD events and for different severity levels of OA by age and sex.
The present study has some limitations that should be acknowledged. Our administrative database does not include information on some cardiovascular risk factors, such as smoking and diet. However, these factors have not been shown to be related to OA and, therefore, are not expected to be confounders of the relationship. In addition, the results were adjusted for COPD, which is correlated with smoking and might reduce the effect of smoking in these relationships. Some acute MI deaths that occurred at home or in the hospital emergency care units were not captured in our study; however, these would not create any differential misclassification. Another limitation of this study is that we have defined OA using ICD diagnostic codes; therefore, both false-negatives and false-positives may occur due to misdiagnosis or incorrect recording in the administrative forms. However, these diagnostic criteria were previously validated ([46, 47]). Harrold et al () estimated the positive predictive value of administratively coded OA in the general population at 62%. We used the case definition that required 2 physician's visits in 2 years or 1 hospital diagnosis, which minimized false-positives in OA diagnosis. The effect of false-negatives in this study will be small, since we have selected non-OA individuals who never had a diagnosis of OA from 1991 to 2009, and we have deleted the prevalent CVD cases using any diagnosis either in the hospital or in the physician's visit before baseline. The misclassifications due to false-positives and -negatives are nondifferential in this study. BMI is a confounder of the association studied and to control for confounding by BMI, we imputed BMI from the CCHS data. Although the imputed values of BMI may not reflect the true distribution in the sample, the effect on the results is probably small given that we imputed BMI by matching on age, sex, OA, and CVD status. As expected, BMI showed a positive association with CVD in the multivariable models.
The exploration of CVD risks among individuals with OA is a promising and important area of research from a public health perspective. Although there is recognition of the high prevalence of OA among the elderly, there has been minimal work done in studying CVD outcomes among OA patients. Our work provides new information by a closer examination of cardiovascular complications among individuals with OA. Our dose-response analyses indicated that the highest RRs were observed among those who underwent TJR, suggesting that persons with an advanced stage of OA had higher risks of CVD, IHD, and CHF than those with less advanced OA. The biologic explanation for the higher risk of CVD overall, and specifically IHD other than MI and CHF, among individuals with OA has yet to be investigated. Although this study was not designed to explain the underlying mechanism, several possible causal paths can be hypothesized. Chronic inflammation, muscle weakness, reduced mobility, and NSAID use are common among individuals with OA, and are also risk factors for CVD. In the present study, we were unable to adjust for these variables; therefore, these results should be interpreted with caution. It should be noted, however, that these factors are not confounders; rather, they may be considered as intermediate variables in the causal path between OA and CVD. Examining the effect of adjusting for these factors in future studies might help elucidate the causal mechanisms for the observed associations.
Despite several limitations, this large, longitudinal study has allowed us to identify statistically significant and biologically plausible relationships that provide a rationale for further biologic, physiologic, and epidemiologic studies of cardiovascular outcomes in persons with OA. The findings suggest that OA may be associated with an increased risk of CVD in a broadly representative population-based context. Specifically, our results indicate that women with OA, irrespective of age, and older men with OA had higher risks of CVD, especially for IHD other than MI and CHF, than age-matched men and women without OA. Further confirmation of these findings in future studies is needed before specific recommendations for new standards of care in OA can be offered.
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. Mr. Rahman 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. Rahman, Kopec, Anis, Cibere, Goldsmith.
Acquisition of data. Rahman, Kopec.
Analysis and interpretation of data. Rahman, Kopec.