Open Forum Infectious Diseases · 2019 · 15 citations · 32 references
MedicineCommunity HealthCommunity MedicineEpidemiologyFalls PreventionPhysical ActivityBone HealthFall RiskFear Of FallingFracture RiskHiv EpidemiologyOsteoporosisBone Fracture RiskBone Mineral DensityBone Mineral Density ScreeningBone Mineral Density TestingBone Quality AnalysisChi-square TestFalls EpidemiologyQuantitative Ultrasound
Abstract Background People with HIV-1 (PWH) exhibit a high fall incidence and increased fracture risk. As little is known about fall frequency and associated factors in PWH residing in lower-middle-income countries (LMIC), we investigated fall frequency, bone quality, and factors associated with fall history in a South African cohort. Methods Fifty PWH without obvious predisposing factors for mobility impairments attending 2 public primary care clinics in the Western Cape region participated. Demographic, clinical, and physical performance data were collected. Falls were assessed retrospectively over 12 months. Mobility and balance were evaluated using a physical performance battery. Bone mineral density was screened using quantitative ultrasound (QUS). Associations between variables and falls grouping were analyzed using chi-square tests, t tests, and Mann-Whitney U tests, and effect sizes (ES) were calculated. Results Thirty-four percent of PWH (median age, 36.6 years) reported falling during the past year, and 41.2% of fallers reported multiple falls. Fallers had more mobility problems (P = .013), higher fear of falling (P = .007), higher fracture history (P = .003), worse balance performance (P < .001), higher proportions of detectable viral loads (P = .021), and poorer bone quality (P = .040). Differences were of medium to large ES. Conclusions This exploratory study is the first to show that relatively young South African PWH without obvious predisposing factors for gait and balance impairments experience falls. The observed fall-associated factors warrant further research using larger samples and longitudinal designs to ascertain fall predictors within this population.
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Statistical Power Analysis for the Behavioral Sciences
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