Study Design.: Prospective cohort study. Objective.: Estimate the prevalence of spondylolisthesis and determine the factors associated with higher or lower prevalence among men aged 65 years or older. Summary of Background Data.: Spondylolisthesis prevalence is reported to increase with age and to be higher among women than men. Among women aged ≥65 years, prevalence was estimated to be 29%, but no estimates among men of this age have been reported. Methods.: Lateral lumbar spine radiographs were obtained at baseline and a follow-up visit in the Osteoporotic Fractures in Men (MrOS) study, a cohort of community dwelling men ages ≥65 years. Average time between radiographs was 4.6 (±0.4) years. For the present study, 300 men were sampled at random at baseline. Of these, 295 had a usable baseline radiograph; 190 surviving participants had a follow-up radiograph. Spondylolisthesis was defined as a forward slip ≥5%. Progression was defined as a 5% increase in slip severity on the follow-up radiograph. Associations of spondylolisthesis prevalence with baseline characteristics were estimated with age-adjusted prevalence ratios and 95% confidence intervals from log binomial regression models. Results.: The mean (SD) age of the men studied was 74 (±6) years. Prevalence of lumbar spondylolisthesis was 31%. Spondylolisthesis was observed at the L3/4, L4/5, and L5/S1 levels. In 96% with spondylolisthesis, only one vertebral level was involved. The degree of slip ranged from 5% to 28%, and nearly all listhesis was classified as Meyerding grade I. During follow-up, 12% of men with prevalent spondylolisthesis had progression; 12% without baseline spondylolisthesis had new onset. Prevalence did not vary by height, BMI, smoking history, diabetes, or heart disease. However, men with spondylolisthesis more often reported higher levels of physical activity or walking daily for exercise than men without spondylolisthesis. Conclusion.: Spondylolisthesis may be more common among older men than previously recognized.
- Numerical simulation
- Patient-specific modelling