Assessing the contributions of modifiable risk factors to serious falls and fragility fractures among older persons living with HIV

Author:

Womack Julie A.12ORCID,Murphy Terrence E.3ORCID,Leo‐Summers Linda45,Bates Jonathan16,Jarad Samah7,Gill Thomas M.5ORCID,Hsieh Evelyn15,Rodriguez‐Barradas Maria C.8,Tien Phyllis C.9,Yin Michael T.10,Brandt Cynthia A.16,Justice Amy C.15

Affiliation:

1. VA Connecticut Healthcare System West Haven Connecticut USA

2. Yale School of Nursing West Haven Connecticut USA

3. Department of Public Health Sciences Pennsylvania State University College of Medicine Hershey Pennsylvania USA

4. Yale School of Medicine New Haven Connecticut USA

5. Department of Internal Medicine Yale School of Medicine New Haven Connecticut USA

6. Section of Biomedical Informatics and Data Science Yale School of Medicine New Haven Connecticut USA

7. Department of Emergency Medicine Yale School of Medicine New Haven Connecticut USA

8. Infectious Diseases Section, Michael E DeBakey VA Medical Center, and Department of Medicine Baylor College of Medicine Houston Texas USA

9. Department of Veterans Affairs University of California San Francisco California USA

10. Department is Medicine, Columbia University Medical Center New York New York USA

Abstract

AbstractBackgroundAlthough 50 years represents middle age among uninfected individuals, studies have shown that persons living with HIV (PWH) begin to demonstrate elevated risk for serious falls and fragility fractures in the sixth decade; the proportions of these outcomes attributable to modifiable factors are unknown.MethodsWe analyzed 21,041 older PWH on antiretroviral therapy (ART) from the Veterans Aging Cohort Study from 01/01/2010 through 09/30/2015. Serious falls were identified by Ecodes and a machine‐learning algorithm applied to radiology reports. Fragility fractures (hip, vertebral, and upper arm) were identified using ICD9 codes. Predictors for both models included a serious fall within the past 12 months, body mass index, physiologic frailty (VACS Index 2.0), illicit substance and alcohol use disorders, and measures of multimorbidity and polypharmacy. We separately fit multivariable logistic models to each outcome using generalized estimating equations. From these models, the longitudinal extensions of average attributable fraction (LE‐AAF) for modifiable risk factors were estimated.ResultsKey risk factors for both outcomes included physiologic frailty (VACS Index 2.0) (serious falls [15%; 95% CI 14%–15%]; fractures [13%; 95% CI 12%–14%]), a serious fall in the past year (serious falls [7%; 95% CI 7%–7%]; fractures [5%; 95% CI 4%–5%]), polypharmacy (serious falls [5%; 95% CI 4%–5%]; fractures [5%; 95% CI 4%–5%]), an opioid prescription in the past month (serious falls [7%; 95% CI 6%–7%]; fractures [9%; 95% CI 8%–9%]), and diagnosis of alcohol use disorder (serious falls [4%; 95% CI 4%–5%]; fractures [8%; 95% CI 7%–8%]).ConclusionsThis study confirms the contributions of risk factors important in the general population to both serious falls and fragility fractures among older PWH. Successful prevention programs for these outcomes should build on existing prevention efforts while including risk factors specific to PWH.

Funder

National Center for Advancing Translational Sciences

National Institute of Arthritis and Musculoskeletal and Skin Diseases

National Institute of Nursing Research

National Institute on Aging

National Institute on Alcohol Abuse and Alcoholism

Publisher

Wiley

Subject

Geriatrics and Gerontology

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