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C-Reactive Protein, Bone Strength, and Nine-Year Fracture Risk: Data From the Study of Women’s Health Across the Nation (SWAN)
Associated Data
Abstract
Higher levels of C-reactive protein (CRP), an inflammatory marker, are associated with increased fracture risk, although previous studies on CRP and bone mineral density (BMD) have yielded conflicting results. We aimed to test the hypotheses that composite indices of femoral neck strength relative to load, which are inversely associated with fracture risk, would also be inversely associated with CRP, and would explain part of the association between CRP and fracture risk. We analyzed data from a multisite, multiethnic prospective cohort of 1872 community-dwelling women, premenopausal or early perimenopausal at baseline. Femoral neck composite strength indices in three failure modes were calculated using dual-energy X-ray absorptiometry (DXA)-derived femoral neck width (FNW), femoral neck axis length (FNAL), femoral neck BMD and body size at baseline, as BMD*FNW/weight for compression strength, BMD*(FNW)2/(FNAL*weight) for bending strength, and BMD*FNW*FNAL/(height*weight) for impact strength. Incident nondigital, noncraniofacial fractures were ascertained annually over a median follow-up of 9 years. In analyses adjusted for age, race/ethnicity, diabetes, menopause transition stage, body mass index, smoking, alcohol use, physical activity, medications, prior fracture, and study site, CRP was associated inversely with each composite strength index (0.035–0.041 SD decrement per doubling of CRP, all p< 0.001), but not associated with femoral neck or lumbar spine BMD. During the follow-up, 194 women (10.4%) had fractures. In Cox proportional hazards analyses, fracture hazard increased linearly with loge(CRP), only for CRP levels ≥ 3 mg/L. Addition of femoral neck or lumbar spine BMD to the model did not attenuate the CRP-fracture association. However, addition of any of the composite strength indices attenuated the CRP-fracture association and made it statistically nonsignificant. We conclude that fracture risk increases with increasing CRP, only above the threshold of 3 mg/L. Unlike BMD, composite strength indices are inversely related to CRP levels, and partially explain the increased fracture risk associated with inflammation.
Introduction
Chronic inflammation is implicated in the pathophysiology of a wide array of conditions including cardiovascular disease,(1) diabetes mellitus,(2) dementia,(3) and age-related macular degeneration.(4) Mounting evidence suggests that inflammation also has a deleterious influence on skeletal health: osteoporosis is more prevalent in patients with chronic inflammatory diseases such as rheumatoid arthritis,(5) systemic lupus erythematosus,(6) inflammatory bowel disease,(7) and chronic obstructive pulmonary disease, independent of glucocorticoid use.(8) Even in the absence of chronic inflammatory diseases, higher levels of systemic inflammatory markers, such as high-sensitivity C-reactive protein (CRP), are associated with greater risk of fragility fracture.(9–13)
Despite the CRP-fracture link, an inverse association between CRP (a robust marker of systemic inflammation) and bone mineral density (BMD) as measured by dual-energy X-ray absorptiometry (DXA) has not been universally reported.(9,11,14–17) One plausible explanation for the less consistent relation between CRP and BMD is that other factors, both skeletal and nonskeletal, contribute to fracture occurrence; estimates are that BMD alone accounts for only 1.7 to 7.4 percent of fracture risk.(18,19) Bone size also contributes to bone structural strength (just as the strength of engineering structures depend on both material density and structure size),(20,21) and body size determines the fracture forces that bone is exposed to in a fall.(22) Thus, composite indices of femoral neck strength that integrate DXA-derived 2D projected BMD, bone size, and (in light of the “supply and demand balance”) body size,(23) are inversely associated with incident hip fracture risk in community-dwelling older Caucasian women(23) and in young U.S. Caucasian and Chinese adults,(24) and have been used as a measure of femoral neck strength.(25–28) Unlike BMD, which does not explain interracial variation in fracture risks, and fails to correctly stratify risk across ethnic groups,(29) femoral neck composite strength indices do correctly stratify fracture risk across ethnic groups.(30) In fact, these indices, unlike BMD, can predict fragility fracture risk in middle-aged women without requiring knowledge of the woman’s race/ ethnicity.(31) Furthermore, the increased fracture risk associated with diabetes, although inconsistent with higher BMD in diabetes,(32) is consistent with the lower composite strength indices seen in diabetics relative to nondiabetics.(33)
We therefore designed a study to examine three questions:
- What are the cross-sectional relations between CRP and each of five candidate bone strength measures (femoral neck BMD, lumbar spine BMD, and the three femoral neck composite strength indices)?
- What is the relation between CRP and incident fracture hazard (rate)?
- Do lower values of (any of the five) bone strength measures in the presence of high CRP explain the association between high CRP and increased fracture hazard?
We hypothesize that CRP associations with the femoral neck composite strength indices will be consistent with CRP-fracture-risk associations (ie, that higher values of CRP will be associated with lower values of composite strength indices) and that lower values of femoral neck composite strength indices will explain a large part of the association between high CRP and high fracture risk.
Subjects and Methods
Study participants
Participants are women from the Study of Women’s Health Across the Nation (SWAN), a multicenter, multiethnic longitudinal study of the biological and psychosocial changes that occur during the menopausal transition. Seven participating clinical sites used either community-based or population based sampling frames. A screening survey was conducted in 16,065 women between 1995 to 1997 to assess eligibility and to collect health, reproductive, demographic, and lifestyle data.(34) Cohort entry criteria, in brief, were as follows: age 42 to 53 years, with intact uterus and at least one ovary, not using sex steroid hormones at enrollment, had at least one menstrual period in the 3 months prior to screening, and self-identified as either Caucasian, African-American, Hispanic, Chinese, or Japanese. Each SWAN site recruited at least 450 eligible women into the cohort in 1996 and 1997, resulting in a inception cohort of 3302 women. (34,35)
Five sites (Boston, Detroit, Pittsburgh, Los Angeles, and Oakland) collected DXA scans of the hip and lumbar spine in all but 46 participants who weighed more than 136 kg (the scanner weight limit); they constituted the SWAN Bone Cohort. All five sites enrolled Caucasians, and each site also enrolled women belonging to one prespecified minority ethnic group: African American in Boston, Detroit, and Pittsburgh; and Japanese and Chinese in Los Angeles and Oakland, respectively. The SWAN Hip Strength Sub-Study, the focus of this report, measured femoral neck size using archived hip DXA scans from the 1960 women in the SWAN bone cohort who had a baseline and two or more follow-up scans by follow-up visit 10 (2006–2007). At baseline, 20 women did not get either bone size or body size measurements and 68 women either missed CRP measurements or were deemed to have acute inflammation (see below), leaving 1872 women in the analytic sample (931 Caucasian, 501 African American, 227 Japanese, and 213 Chinese). All protocols were approved by Institutional Review Boards at each site and all participants gave written informed consent.
Assessment of BMD and composite indices of femoral neck strength
Using the OsteoDyne Hip Positioner System (Osteodyne Inc., Morrisville, NC, USA), DXA scans of the posterior-anterior lumbar spine and total hip were acquired at the baseline visit. Hologic QDR 4500 models were used in Boston, Detroit, and Los Angeles, and QDR 2000 scanners were used in Pittsburgh and Oakland (Hologic Inc., Waltham, MA). A standard quality-control program, conducted in collaboration with Synarc, Inc. (Newark, CA, USA), included daily phantom measurements, 6-month cross-calibration with a circulating anthropomorphic spine standard, local site review of all scans, central review of scans that met problem-flagging criteria, and central review of 5% random sample of scans. The 2D-projected (areal) BMD in the femoral neck and lumbar spine were recorded. Two bone size measurements were made on archived baseline hip scans using pixel dimensions provided by the manufacturer: femoral neck axis length (FNAL) and femoral neck width (FNW) (Fig. 1).(23) Composite femoral neck strength indices were computed using height, weight, FNAL, FNW, and femoral neck BMD (Fig. 1). Compression strength index (CSI) reflects the ability to withstand axial compressive loads, bending strength index (BSI) reflects ability to withstand bending forces, and impact strength index (ISI) reflects the ability to absorb the energy of impact in a fall from standing height.(23) To examine reproducibility of the strength indices, 20 women were scanned twice after repositioning; the intraclass correlation coefficient for each index was greater than 0.98.
Femoral neck size measurements and formulae to compute composite femoral neck strength indices. AB is the femoral neck axis length (FNAL), the distance from the base of the greater trochanter to the apex of the femoral head, and DE is the femoral neck width (FNW), the smallest thickness of the femoral neck along any line perpendicular to the femoral neck axis. C is where the femoral neck axis meets the inner pelvic rim. Composite femoral neck strength indices were computed using the following formulae, where BMD refers to the areal (projected 2D) bone mineral density in the femoral neck obtained from DXA:
- Compression Strength Index (CSI)= BMD × FNW/Weight
- Bending Strength Index (BSI) = BMD × FNW2/(FNAL × Weight)
- Impact Strength Index (ISI) = BMD × FNW × FNAL/(Height × Weight)
All three indices were recorded in units of g/kg-m. With BMD measured in g/cm2, FNW and FNAL in cm, weight in kg, height in meters; CSI and BSI were scaled by 100 to get values in units of g/kg-m.
Assessment of CRP
Blood drawn at the baseline SWAN visit was assayed for high-sensitivity CRP at Medical Research Laboratories (Highland Heights, KY, USA), using an ultrasensitive rate immunonephelo-metric method with a lower limit of detection of 0.3 mg/L (BN100; Dade-Behring, Marburg, Germany). The CRP assay within-run coefficient of variation (CV) at CRP concentrations of 0.5 and 22.0 mg/L were 10–12% and 5–7%, respectively.(36) CRP measurements from 30 women were deemed indicative of acute inflammation and excluded, because repeat CRP at the next SWAN visit was at least 5 mg/L lower than the baseline measurement and no greater than 3 mg/L.
Incident fracture ascertainment and classification
During each of nine annual follow-up visits, fractures since the previous visit were self-reported using a standardized interviewer-administered questionnaire. In all years, the number of fractures, body site(s), and how fractures occurred were recorded. SWAN initiated collection of the date of fracture at follow-up visit 6. Because dates of fractures were not collected in the first six follow-ups, they were imputed using the midpoint between the participant’s previous and index visits. Fractures reported at visit 6 and later were confirmed by reviewing medical records. Medical records were available for 85% of fractures and of these, only four fractures (3.8%) could not be confirmed. We excluded from all analyses factures not typically associated with osteoporosis, in particular fractures of the face, skull, fingers, and toes.(37,38) We created two categories of fractures: all fractures and minimum-trauma fractures. Minimum-trauma fractures excluded those that occurred due to a fall from height greater than 6 inches; in a motor vehicle accident; while moving fast (eg, bicycling or skating); while playing sports; or from impact with heavy or fast-moving projectiles.
Other measurements
Participants provided the following information at baseline: age (years), race/ethnicity, menopause transition stage (premenopause or early perimenopause: no changes versus some changes in regularity of menses but with no gaps of ≥3 months), physical activity level (summary score combining intensity with frequency of active living, home, and recreational physical activity from modified Baecke interview(39), prescription medications used, vitamin D and calcium supplement use, alcohol consumption (“abstainer,” “infrequent: not abstainer, but ≤1 drink per week,” “light to moderate: >1 drink per week, but ≤1 per day,” and “heavy: >1 drink per day”), smoking history, and comorbidities. Women who reported use of diabetes medications or had fasting serum glucose ≥ 126 mg/dL were classified as diabetic. Height and weight were measured and used to compute body mass index (BMI). Serum glucose was measured from blood drawn after an overnight fast, using a hexokinase-coupled reaction (Roche Molecular Biochemicals Diagnostics, Indianapolis, IN, USA). During each of the follow-up visits, information on use of medications was collected using interviewer-administered questionnaires.
Statistical analysis
Analyses were undertaken to answer the following three questions.
- What are the cross-sectional relationships between CRP and each of the five bone strength measures (femoral neck BMD, lumbar spine BMD, and the three femoral neck composite strength indices)?
- What is the relationship between CRP and incident fracture hazard (rate)?
- Do lower values of any of the five bone strength measures explain the association between high CRP and greater risk of any fracture or of minimum trauma fracture?
We first used nonparametric, locally weighted scatter plot smoothing (LOESS) plots to examine the functional forms of the association between CRP and each of the strength measures (femoral neck BMD, lumbar spine BMD, and three composite strength indices) at baseline. LOESS plots revealed that relation-ships of loge(CRP) with each of the strength measures was approximately linear (Fig. 2). We then fitted multiple linear regression models to each strength measure as a linear function of loge(CRP) adjusted for: baseline measurements of age (continuous); race/ethnicity; diabetes; menopause transition stage (premenopause versus early perimenopause); smoking status (never, past, current); alcohol use categories (abstainer, infrequent, light-to-moderate, heavy); level of physical activity (above median versus below median); use (yes versus no) of medications from the following five classes (one indicator variable for each): supplementary vitamin D, supplementary calcium, bone-active medications (oral steroids, chemotherapy for breast cancer, aromatase inhibitors, antiepileptics), nonsteroidal anti-inflammatory drugs, and central nervous system active medications (antidepressants, antiepileptics, sedatives, soporifics); ever previous use (yes versus no) of oral steroids; ever previous use of sex steroids (oral estrogen/progesterone, estrogen patches, birth control pills); history of prior fracture as an adult (after age 20 years); and study site. Use of osteoporosis medications (bisphosphonates, selective estrogen receptor modulators, calcitonin, parathyroid hormone, or vitamin D in pharmacological doses) at baseline was reported by only one participant, and therefore not included in the model.
LOESS plots of bone strength measures (femoral neck and lumbar spine areal bone mineral density, and femoral neck composite strength indices) against natural log-transformed (CRP) (n = 1872). CRP=C-reactive protein; CSI=compression strength index; BSI=bending strength index; ISI=impact strength index; BMD=areal (2D projected) bone mineral density.
We initially did not control for BMI because obesity is a major risk factor for high CRP,(40–42) and adjusting for it would attenuate power to detect CRP effects.(43) However, because BMI is also positively associated with BMD via CRP-independent mechanisms such as loading,(22) it is a potential confounder of CRP–bone strength associations. Therefore, in a next step, we added BMI to the models as a continuous (linear) term, plus squared (quadratic) term to allow for known nonlinear associations between BMI and CRP,(40,41,44) plus interaction terms between continuous BMI and race/ethnicity because of large ethnic/racial differences in BMI. We next tested the interaction between CRP and race/ethnicity.
To address the second question, we first used restricted cubic spline analysis to examine the functional form of the association between baseline CRP and incident fracture hazard (rate) over the 9-year follow-up. The restricted cubic spline plot demonstrated that the relationship between loge(CRP) and loge(fracture hazard) was piecewise linear with two inflection points (change of slope) at loge(CRP) values of −0.7 and 1.1 (corresponding to CRP values of 0.5 and 3.0 mg/L, respectively) (Fig. 3). We then employed Cox proportional hazard regression to model loge(fracture hazard) as a piecewise linear function of loge(CRP) with two fixed knots at CRP of 0.5 mg/L and 3 mg/L, after we had verified the proportional hazards assumption for CRP. We adjusted for the set of baseline covariates listed above as well as use on at least two consecutive visits during follow up (yes versus no) of medications from the following four classes: sex steroid hormones; osteoporosis medications; oral steroids; and other bone-active medications (chemotherapy, aromatase inhibitors, antiepileptics) as time-invariant covariates. The change in CRP-fracture association (slope) at the knot at CRP of 3 mg/L was statistically significant in both unadjusted and fully-adjusted models (p = 0.03 and 0.01, respectively) but the knot at CRP of 0.5 mg/L was not statistically significant in either model (p = 0.14 and 0.12, respectively); therefore, the knot at 0.5 was dropped.
Restricted cubic spline plot of the natural log of the relative hazard of fracture against natural log-transformed CRP level (measured in mg/L). CRP = C-reactive protein.
To test if any of the five bone strength measures (femoral neck BMD, lumbar spine BMD, and three composite strength indices) explain the association between CRP and fractures (question 3), we added each of the strength measures to the adjusted model, one at a time. Unlike BMD, the composite indices assess strength relative to body size; therefore, to make the comparisons between BMD and the composite indices fairer, we added BMI to the models with BMD and examined if BMD and BMI together better explain the CRP–fracture association.
We performed all the analyses for each of two outcomes: all fractures and minimum trauma fractures. For analyses using nontraumatic fractures as an outcome, follow-up time was censored at the time of the first trauma-associated fracture.(45) We also tested the interaction between CRP and race/ethnicity in the analyses of CRP and fracture risk.
A total of 86 (4.5%) women had one or more covariates missing and the missing values were imputed by single imputation using the expectation maximization (EM) algorithm.(46)
All analyses were conducted using SAS version 9.3 (SAS Institute, Inc., Cary, NC, USA). Two-sided p < 0.05 was considered statistically significant.
Results
The study sample (n = 1872) was representative of the complete Swan bone cohort (n = 2413) with respect to baseline clinical characteristics (Table 1). Of 1872 women included in the analysis, 569 (30.4%) had CRP 3 mg/L or higher, and 141 (7.5%) had CRP 10 mg/L or higher.
Table 1
Baseline Characteristics of SWAN Bone Strength Study Sample and SWAN Bone Cohorta
| Characteristics | Study sample (n = 1872) | Bone cohort (n = 2413) |
|---|---|---|
| Age (years) | 45.9 ±2.7 | 45.8 ±2.7 |
| Height (cm) | 162.3 ±6.5 | 162.5 ±6.6 |
| Weight (kg) | 73.0 ±19.4 | 74.3 ±21.3 |
| Race/ethnicity, n (%) | ||
| Caucasian | 931 (49.7) | 1196 (49.6) |
| African-American | 501 (26.8) | 686 (28.4) |
| Chinese | 213 (11.4) | 250 (10.4) |
| Japanese | 227 (12.1) | 281 (11.7) |
| Body mass index, n (%) | ||
| Low (<22 kg/m2) | 411 (22.1) | 512 (21.5) |
| Normal (22–25 kg/m2) | 430 (23.2) | 546 (22.9) |
| Overweight (25–30 kg/m2) | 458 (24.7) | 571 (23.9) |
| Obese (≥30 kg/m2) | 557 (30.0) | 756 (31.7) |
| Menopause transition stage, n (%)a | ||
| Premenopausal | 1056 (56.4) | 1288 (54.1) |
| Early perimenopausal | 816 (43.6) | 1094 (45.9) |
| Smoking status, n (%) | ||
| Never smoked | 1115 (60.0) | 1383 (57.8) |
| Ex-smoker | 467 (25.1) | 619 (25.9) |
| Current smoker | 277 (14.9) | 393 (16.4) |
| Alcohol consumption, n (%)b | ||
| Abstainer | 962 (51.4) | 1244 (51.8) |
| Infrequent | 170 (9.1) | 220 (9.2) |
| Light | 486 (26.0) | 607 (25.3) |
| Heavy | 252 (13.5) | 332 (13.8) |
| Physical activity level | ||
| Above median | 902 (49.6%) | 1161 (49.6) |
| Below median | 917 (50.4%) | 1179 (50.4) |
| Medications, n (%) | ||
| Bone-active medicationsc | 42 (2.2) | 56 (2.3) |
| Supplementary vitamin D | 723 (38.7) | 917 (38.2) |
| Supplementary calcium | 846 (45.2) | 1066 (44.4) |
| CNS active medicationsc | 195 (10.4) | 264 (10.9) |
| NSAIDs | 192 (10.3) | 246 (10.2) |
| Diabetes mellitus, n (%)d | 89 (4.8) | 133 (5.5) |
| Inflammatory conditions, n (%) | 109 (5.8) | 152 (6.3) |
| Loge(C reactive protein in mg/L)e | 0.3 ±1.3 | 0.4 ± 1.4 |
| Femoral neck axis length (cm) | 9.0 ±0.5 | − |
| Femoral neck width (cm) | 2.7 ±0.2 | − |
| Femoral neck bone mineral density (g/cm2) | 0.84 ±0.14 | 0.84 ±0.13 |
| Spine bone mineral density (g/cm2) | 1.07 ±0.13 | 1.07 ±0.13 |
| Compression strength index (g/kg-m) | 3.3 ±0.6 | − |
| Bending strength index (g/kg-m) | 1.0 ±0.2 | − |
| Impact strength index (g/kg-m) | 0.18 ±0.04 | − |
| History of prior fracture after age 20 years, n (%) | 340 (18.1) | 457 (19.0) |
Mean ± SD are shown for continuous variables and number of participants and percentage are shown for categorical variables.
SWAN = Study Participants in the Study of Women’s Health; CNS = central nervous system; NSAID = nonsteroidal anti-inflammatory drugs; CRP = C- reactive protein.
Baseline associations between CRP and strength measures
In multiple linear regression adjusted for covariates, CRP was inversely associated with each of the three composite strength indices (compression, bending, and impact): Each doubling of CRP (from 3 to 6, or 4 to 8, or 5 to 10, for example) was associated with 0.16 to 0.22SD reductions in the strength indices (Table 2). In sharp contrast, CRP was associated positively with both femoral neck and lumbar spine BMD. Addition of BMI terms to the models changed the direction of the CRP-BMD associations, though they were not statistically significant (p = 0.08 for femoral neck BMD and p = 0.09 for lumbar spine BMD). On the other hand, CRP remained inversely and significantly associated with the composite strength indices after inclusion of controls for BMI (Table 2).
Table 2
Adjusted Associations of Serum C-Reactive Protein Level With Bone Strength Measures at Baseline (n = 1872)
| Bone strength measure | Effect size per doubling of C-reactive proteina | 95% confidence interval | p |
|---|---|---|---|
| Femoral neck bone mineral density | 0.114 | (0.092 to 0.137) | <0.001 |
| Lumbar spine bone mineral density | 0.082 | (0.057 to 0.108) | <0.001 |
| Compression strength index | −0.209 | (−0.230 to −0.187) | <0.001 |
| Bending strength index | −0.162 | (−0.184 to −0.140) | <0.001 |
| Impact strength index | −0.216 | (−0.238 to −0.195) | <0.001 |
| After additional adjustment for BMIb | |||
| Femoral neck bone mineral density | −0.022 | (−0.046 to 0.002) | 0.08 |
| Lumbar spine bone mineral density | −0.025 | (−0.054 to 0.004) | 0.09 |
| Compression strength index | −0.036 | (−0.057 to −0.015) | <0.001 |
| Bending strength index | −0.035 | (−0.059 to −0.011) | 0.005 |
| Impact strength index | −0.041 | (−0.063 to −0.020) | <0.001 |
Values adjusted for age, race/ethnicity, menopause status, smoking status, alcohol use, physical activity, use of supplementary vitamin D, supplementary calcium, bone-active medications, central nervous system–active medications, nonsteroidal anti-inflammatory drugs, ever use of oral steroids, ever use of sex steroid hormones, diabetes, history of previous fractures, and study site.
We conducted a sensitivity analysis, in which, instead of adding controls for BMI, we added a control for body weight. The CRP-CSI association remained strong (effect size = −0.066, p<0.001). Further additional adjustment for body height did not substantially change the association (effect size =−0.052, p<0.001). Similar findings were obtained for the other two composite indices, BSI and ISI (data not shown), confirming the robustness of the CRP associations with the composite strength indices.
To further test how much body weight was driving the CRP association with strength indices, we examined the cross-sectional associations of CRP with the product of femoral neck BMD and FNW. The latter represents the compression strength index without normalization by body weight. Further, to investigate the contribution of bone size (relative to body size) to the association between CRP and composite strength indices, we separately examined the cross-sectional associations of CRP with the relative bone size factors in the three composite indices (FNW/weight for compression, FNW2/(FNAL*weight) for bending, and (FNW*FNAL)/(height*weight) for impact. Models adjusted for all covariates in Table 2, including the BMI terms. CRP was significantly and inversely associated with the product of femoral neck BMD and FNW (−0.040 SD decrement per doubling of CRP, p = 0.002) and two of the three relative size factors in the composite indices (p = 0.01 for compression strength,p = 0.10 for bending strength, and p = 0.005 for impact strength), suggesting that relative bone size also contributes to the significant association between CRP and the composite strength indices.
Association between baseline CRP and any incident fracture
After median follow-up of 9.0 (interquartile range, 8.9–9.1) years, 194 women (10.4%) had at least one fracture, at a rate of 12.5 per 1000 person-years. In Cox proportional hazard regression of loge(fracture hazard) as a piecewise linear function of loge(CRP) with a fixed knot at CRP of 3 mg/L, fracture hazard was not associated with CRP for values of CRP < 3, but fracture hazard increased significantly with CRP, for values of CRP ≥ 3 (Table 3). Every doubling of CRP (at levels above 3 mg/L) was associated with 25% relative increment in fracture hazard (95% confidence interval [CI], 3% to 53%). Addition of femoral neck or lumbar spine BMD to the model did not attenuate this association, but the addition of any of the three femoral neck composite strength indices attenuated the CRP-fracture association by 24% to 36% (relative hazard fell from 1.25 to between 1.16 and 1.19), and made it nonsignificant (Table 3). Addition of lumbar spine BMD together with BMI did attenuate the CRP-fracture association, but not as much as any of the composite strength indices (Table 3).
Table 3
Adjusted Relative Hazard for Any Fracture and for Minimum-Trauma Fracture per Doubling of Serum CRP Level Above 3 mg/L During a Median Follow-Up of 9.0 Years, Before and After Additional Adjustment for Bone Strength Measures and BMI (n = 1872)
| HR (95% CI) per doubling of CRP above 3 mg/L | p | |
|---|---|---|
| Outcome: any fracture | ||
| Fully adjusted modela | 1.25 (1.03–1.53) | 0.03 |
| Full model + spine BMD | 1.25 (1.03–1.52) | 0.02 |
| Full model + spine BMD + BMI termsb | 1.21 (0.98–1.50) | 0.08 |
| Full model + femoral neck BMD | 1.33 (1.09–1.62) | 0.005 |
| Full model + femoral neck BMD + BMI termsb | 1.24 (1.003–1.54) | 0.047 |
| Full model + compression strength index | 1.16 (0.94–1.42) | 0.16 |
| Full model + bending strength index | 1.19 (0.97–1.45) | 0.10 |
| Full model + impact strength index | 1.17 (0.96–1.44) | 0.13 |
| Outcome: minimum-trauma fracture | ||
| Fully adjusted modela | 1.42 (1.08–1.86) | 0.01 |
| Full model + spine BMD | 1.40 (1.08–1.83) | 0.01 |
| Full model + spine BMD + BMI termsb | 1.36 (1.02–1.81) | 0.04 |
| Full model + femoral neck BMD | 1.49 (1.13–1.95) | 0.004 |
| Full model + femoral neck BMD + BMI termsb | 1.42 (1.06–1.90) | 0.02 |
| Full model + compression strength index | 1.32 (1.001–1.74) | 0.049 |
| Full model + bending strength index | 1.33 (1.008–1.75) | 0.044 |
| Full model + impact strength index | 1.34 (1.02–1.77) | 0.04 |
CRP = C-reactive protein; BMI = body mass index; HR = hazard ratio; CI = confidence interval; BMD = bone mineral density.
Association between baseline CRP and incident minimum-trauma fracture
After the 9-year follow-up, 79 women (4.2%) had at least one minimum-trauma fracture, at a rate of 5.1 per 1000 person-years. For the minimum-trauma fracture outcome, fracture hazard was not associated with CRP for values of CRP under 3 mg/L, but higher CRP predicted greater fracture rate for values of CRP above 3 mg/L (Table 3). Every doubling of CRP (at levels 3 mg/L and above) was associated with 42% relative increment in fracture hazard (95% CI, 8% to 86%). The addition of femoral neck or lumbar spine BMD did not attenuate this association but the addition of any of the composite strength indices reduced the magnitude of the association by 19% to 24% (the relative hazard fell from 1.42 to between 1.32 and 1.34), though the association remained marginally significant. The addition of lumbar spine BMD together with BMI did also comparably attenuate the CRP-fracture association.
Effect modification by race/ethnicity
Race/ethnicity did not modify the association of CRP with any of the five bone strength measures (p=0.20 to 0.98), fracture hazard or minimum-trauma fracture hazard (p =0.28 to 0.85).
Sensitivity analysis
Because some women had very high values of CRP, which could influence the associations of CRP with each of bone strength measures and fracture risk, we conducted a sensitivity analysis, after excluding 141 women (7.5%) who had CRP values equal to or higher than 10 mg/L at baseline. Those who were excluded did not differ in age, height, or the menopause transition stage, but were heavier and more likely to be diabetic and physically inactive. This sensitivity analysis demonstrated almost identical associations between CRP and each of strength measures (Supplementary Table 1) and similar effect sizes with wider confidence intervals in the associations between CRP and all fracture risk (Supplementary Table 2) and diminished effect sizes with wider confidence intervals in the association between CRP and minimum-trauma fracture risk (Supplementary Table 2).
Discussion
As hypothesized, in this multiethnic cohort of women going through the menopause transition, higher serum levels of CRP were associated with lower femoral neck composite strength indices but were not associated significantly with areal BMD in either the femoral neck or the lumbar spine. Baseline levels of CRP were also associated positively with the rate of incident fracture over 9 years of follow up. Every doubling of CRP was associated with a 0.16 to 0.22 SD reduction in strength indices, and at levels above 3 mg/L, every doubling of CRP was also associated with 25% relative increment in fracture rate (hazard) and 42% relative increment in the rate of non-traumatic fracture. The decrement in femoral neck composite strength indices with high CRP explained some but not all of the positive association between CRP and fracture risk.
Our study confirms and extends previous studies that have found strong associations between CRP and fracture risk in older men and women.(9–13) This is the first study to show that inflammation very early in the menopause transition is a major, independent risk factor for fracture, although fracture risk is considerably lower in middle-aged women than in older women. The study also sheds new light on the nature of the CRP-fracture relationship, suggesting the presence of a threshold CRP level for increased fracture risk. Above the threshold, it is not only the presence of inflammation, but also its magnitude that confers increased risk.
Like this study, several previous studies have failed to detect significant associations between high CRP and low BMD.(11,15,17) In fact, one previous study found high CRP to be associated with high BMD.(9) This is surprising because inflammation causes upregulation of osteoclasts and downregulation of osteoblasts, which should result in increased bone resorption,(47,48) and at least one study has documented faster bone loss in the presence of high CRP.(49) Obesity is a primary source of proinflammatory cytokines and chronic inflammation, but excess weight may have opposing effects on bone metabolism.(50–52) We speculate that, in heavier individuals, the detrimental effects of inflammation on bone may be counteracted by increased bone formation secondary to increased mechanical loading due to higher body weight.(53,54) In our study, although high CRP was not associated with low BMD, it was associated strongly with low composite indices of bone strength, suggesting that on balance, the effect of elevated CRP on bone strength relative to load is detrimental.
The importance of bone size to strength has been established,(20,21) and the need to assess bone strength relative to load has also been demonstrated previously.(31,33,55–58) Supplementary analyses of the components of the composite strength indices indicated that absolute compression strength (without normalization by body weight) was significantly associated with CRP, indicating that skeletal load (body weight) is not the primary driver of the CRP association with bone strength relative to load. We also noted significant associations between CRP and bone size relative to body size, thus relative bone size also appears to play an important role in the association between CRP and relative bone strength. Our study also suggests that to account for differences in the size of the load on bone, it may not be enough to simply adjust for body size in an additive, linear model. Inclusion of additive controls for BMI (including linear and quadratic terms, as well as interactions with race/ethnicity) eliminated the unexpected positive association initially seen between CRP and BMD, but did not reveal a significant inverse association between the two. In an additive model, BMD and BMI together explained less of the CRP-fracture association than did the composite strength indices (which include body weight in a multiplicative fashion) on their own (16% versus 25% to 33%).
Lumbar spine BMD explained more of the CRP-fracture association than did femoral neck BMD. Cortical bone loss occurs later than trabecular bone loss in the course of osteoporosis(59); therefore, BMD in the primarily cortical femoral neck may not be sensitive to inflammation, especially in this relatively young cohort. In contrast, lumbar spine, which mostly consists of trabecular bone and is highly vascular, may be more susceptible to inflammation-induced bone fragility.
Our study has some limitations. First, we did not have information on the acuteness of CRP elevation and could not exclude the possibility that some CRP elevations merely reflected acute inflammatory conditions rather than chronic inflammation. However, only 30 women with elevated CRP at the baseline visit had normal CRP values at the first follow-up visit. Their CRP measurements were considered invalid and the women were excluded from the analysis. Sensitivity analyses that excluded women with very high CRP values (>10 mg/L) yielded similar results. The composite strength indices do not take into account bone microstructural aspects (eg, mineralization quality)(60) and hip geometry characteristics (eg, femoral neck-shaft angle).(61) Despite this, the composite indices appear to better assess inflammation-induced bone fragility than the more conventional BMD measure of bone strength. In this study, fractures were self-reported; however, the majority of fractures (all fractures reported after visit 6) were confirmed by medical records review. It is still possible that we overlooked clinically silent vertebral fractures, though the prevalence of vertebral fractures in this young population would be low. Also, the exact date of fracture was not available until follow up visit 7. Finally, this cohort was limited to women, and our findings may not be applicable to men.
Despite these limitations, this study has many strengths. It is the first to demonstrate low bone strength in the presence of chronic inflammation and to determine the magnitude of the inflammation-fracture association explained by low bone strength. Importantly, CRP was measured early in the menopause transition, before the women had experienced substantive drops in circulating estrogen levels, highlighting the early role played by inflammation on bone health. This study adds to the growing evidence that points to the importance of assessing bone strength relative to load, over the assessment of absolute bone strength. Further research is needed to explore other mechanisms by which inflammation could lead to fracture risk, including deleterious changes in bone microarchitecture and increases in fall risk.
Acknowledgments
The Study of Women’s Health Across the Nation (SWAN) is supported by the National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and the NIH Office of Research on Women’s Health (ORWH) (NR004061, AG012505, AG012535, AG012531, AG012539, AG012546, AG012553, AG012554, AG012495). The Hip Strength Through the Menopausal Transition Study is supported by the NIA (AG026463). Additional support for this project was provided by the NIA through R01-AG033067 and P30-AG028748. SI was supported by the Veterans Administration Greater LA Healthcare System Geriatric Research, Education, and Clinical Center, and its Advanced Geriatrics Fellowship. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NIA, NINR, ORWH, VA, or the NIH. We thank the study staff at each site and all the women who participated in SWAN. Clinical Centers: University of Michigan, Ann Arbor, MI (Siobán Harlow, PI, 2011–present; MaryFran Sowers, PI, 1994–2011); Massachusetts General Hospital, Boston, MA (Joel Finkelstein, PI, 1999–present; Robert Neer, PI, 1994–1999); Rush University, Rush University Medical Center, Chicago, IL (Howard Kravitz, PI, 2009–present; Lynda Powell, PI, 1994–2009); University of California, Davis/Kaiser(Ellen Gold, PI); University of California, Los Angeles (Gail Greendale, PI); Albert Einstein College of Medicine, Bronx, NY (Carol Derby, PI, 2011–present; Rachel Wildman, PI, 2010–2011; Nanette Santoro, PI, 2004–2010); University of Medicine and Dentistry–New Jersey Medical School, Newark, NJ (Gerson Weiss, PI, 1994–2004); and the University of Pittsburgh, Pittsburgh, PA (Karen Matthews, PI). NIH Program Office: National Institute on Aging, Bethesda, MD (Winifred Rossi, 2012–present; Sherry Sherman, 1994–2012; Marcia Ory, 1994–2001; National Institute of Nursing Research, Bethesda, MD (Program Officers). Central Laboratory: University of Michigan, Ann Arbor, MI (Daniel McConnell, Central Ligand Assay Satellite Services). Coordinating Center: University of Pittsburgh, Pittsburgh, PA – Maria Mori Brooks, PI, 2012–present; Kim Sutton-Tyrrell, PI, 2001–2012); New England Research Institutes, Watertown, MA (Sonja McKinlay, PI, 1995–2001). Steering Committee: Susan Johnson, Current Chair; Chris Gallagher, Former Chair.
Authors’ roles: Study Concept: ASK, SI, GAG, and JAC. Data analysis: SI. Obtain funding: ASK, GAG, CJC, and JAC. Data interpretation: SI, ASK,GAG,JAC, and CJC. Drafting manuscript: SI. Revising manuscript content: SI, ASK, GAG, JAC, CJC, MED, and YO. Approving final version of manuscript: SI, ASK, GAG, JAC, CJC, MED, and YO. SI takes responsibility for the integrity of the data analysis.
Footnotes
Additional Supporting Information may be found in the online version of this article.
Disclosures
All authors state that they have no conflicts of interest.