Background: Smoking is a risk factor for fracture, but the mechanism by which smoking increases fracture risk is unclear.
Methods: Musculoskeletal health was compared with dual energy X-ray absorptiometry (DXA), high resolution peripheral quantitative computed tomography (HR-pQCT), trabecular bone score, and vertebral fracture assessment in current and past smokers and nonsmokers from a multiethnic study of adults ≥ age 65. Skeletal indices were adjusted for age and weight.
Results: Participants (n = 311) were mean age (±SD) 76.1 ± 6.5 years, mostly female (66.0%) and non-white (32.7% black/39.4% mixed race/26.3% white). Mean pack-years was 34.6 ± 20.4. In men (n = 106), weight and BMI were lower (both p < 0.05) in current vs past smokers. Male smokers consumed half the calcium of never and past smokers. BMD by DXA did not differ by smoking status at any skeletal site in either sex. Current male smokers had 13.5%-15.3% lower trabecular bone score vs never and past smokers (both p < 0.05). By HR-pQCT, trabecular volumetric BMD was 26.6%-30.3% lower and trabeculae were fewer, thinner and more widely spaced in male current vs past and never smokers at the radius (all p < 0.05). Cortical indices did not differ. Tibial results were similar, but stiffness was also 17.5%-22.2% lower in male current vs past and never smokers (both p< 0.05). In women, HR-pQCT trabecular indices did not differ, but cortical porosity was almost twice as high in current vs never smokers at the radius and 50% higher at the tibia (both p < 0.05).
Conclusions: In summary, current smoking is associated with trabecular deterioration at the spine and peripheral skeleton in men, while women have cortical deficits. Smoking may have sex-specific skeletal effects. The consistent association with current, but not past smoking, suggests the effects of tobacco use may be reversible with smoking cessation.
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http://dx.doi.org/10.1016/j.jocd.2020.07.002 | DOI Listing |
Eur J Med Res
January 2025
The Department of Pediatrics, The Third Xiangya Hospital of Central South University, Changsha, 410013, Hunan, China.
Background: The systemic immune-inflammation index (SII) is an emerging marker of inflammation, and the onset of psoriasis is associated with inflammation. The aim of our study was to investigate the potential impact of SII on the incidence rate of adult psoriasis.
Methods: We conducted a cross-sectional study based on the National Health and Nutrition Examination Survey (NHANES) 2011-2014 data sets.
Disabil Rehabil
January 2025
Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
Purpose: To explore associations of environmental and personal factors, participation, and health-related quality of life (HR-QoL) with physical behavior (PB) after subarachnoid hemorrhage (SAH).
Materials And Methods: PB, expressed in duration and distribution of physical activity (PA; walking, running, cycling) and sedentary behavior (SB; lying/sitting) and PA intensity was assessed with the Activ8 accelerometer during 7 days. Environmental and personal factors (social influence, health-condition, illness-perception, self-efficacy, fatigue, mood, kinesiophobia, cognition, coping, sleep), participation and HR-QoL, were assessed with validated questionnaires.
Tob Induc Dis
January 2025
Institute of Medical Science, University of Toronto, Toronto, Canada.
Introduction: There is substantial interest in the association of vaping e-cigarettes with the risk of cancer. We analyzed this risk in different populations by updating the Kings College London (KCL) review to include the period between July 2021 and December 2023.
Methods: We searched six databases and included peer-reviewed human, animal, and cell/ original studies examining the association between e-cigarettes and cancer risk, but we excluded qualitative studies.
Tob Induc Dis
January 2025
Institute of Health and Environment, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea.
Introduction: Smoking behaviors can be quantified using various indices. Previous studies have shown that these indices measure and predict health risks differently. Additionally, the choice of measure differs depending on the health outcome of interest.
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