Inflammatory Markers and Risk of Hip Fracture in Older White Women: The Study of Osteoporotic Fractures †

Abstract Hip fractures are the most devastating consequence of osteoporosis and impact 1 in 6 white women leading to a 2-3 fold increased mortality risk in the first year. Despite evidence of inflammatory markers in the pathogenesis of osteoporosis, few studies have examined their effect on hip fracture. To determine if high levels of inflammation increase hip fracture risk and explore mediation pathways, a case-cohort design nested in a cohort of 4709 white women from the Study of Osteoporotic Fractures was used. A random sample of 1171 women was selected as the subcohort (mean age 80.1 ± 4.2 years) plus the first 300 women with incident hip fracture. Inflammatory markers interleukin-6 (IL-6) and soluble receptors (SR) for IL-6 (IL-6 SR) and tumor necrosis factor (TNF SR1 and TNF SR2) were measured and participants were followed for a median (interquartile range) of 6.3 (3.7, 6.9) years. In multivariable models, the hazard ratio (HR) of hip fracture for women in the highest inflammatory marker level (quartile 4) was 1.64 (95% confidence interval [CI], 1.09-2.48, p trend=0.03) for IL-6 and 2.05 (95% CI, 1.35-3.12, p trend <0.01) for TNF SR1 when compared with women in the lowest level (quartile 1). Among women with 2 and 3-4 inflammatory markers in the highest quartile, the HR of hip fracture was 1.51 (95% CI, 1.07-2.14) and 1.42 (95% CI, 0.87-2.31) compared with women with 0-1 marker(s) in the highest quartile (p trend = 0.03). After individually adjusting for 7 potential mediators, cystatin-C (a biomarker of renal function) and bone mineral density (BMD) attenuated HRs among women with the highest inflammatory burden by 20% and 15%, respectively, suggesting a potential mediating role. Older white women with high inflammatory burden are at increased risk of hip fracture in part due to poor renal function and low BMD

Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

<p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p

Associations of Smoking, Moderate Alcohol Use, and Function: A 20-Year Cohort Study of Older Women

Objective: The objective of this study is to determine whether the health effects of smoking and moderate alcohol use persist with aging. Method: Smoking status, alcohol use, and measures of function and health were obtained from 9,704 women aged ≥65 years at baseline and over 10- and 20-year follow-up periods. Adjusted multiple linear and logistic regression and Cox proportional hazard models estimated associations. Results: Current versus never smokers had worse walking speed, self-reported health, difficulty with instrumental activities of daily living (IADLs), and depression at 10 years and higher death rates at 10 and 20 years. Moderate versus never drinkers had better grip strength, walking speed, self-reported health, and less difficulty with IADLs and were less likely to live in nursing homes at 10 years and die at 10 and 20 years. Discussion: Among aging women over 20 years, smoking is associated with worse physical function, including death, while moderate alcohol use is associated with better outcomes