A population-based study.
To study the prevalence and features of symptomatic degenerative lumbar osteoarthritis in adults.
Lumbar osteoarthritis adversely affects individuals and is a heavy burden. There are limited data on the prevalence of lumbar osteoarthritis.
A representative, multistage sample of adults was collected. Symptomatic degenerative lumbar osteoarthritis was diagnosed by clinical symptoms, physical examinations, and imaging examinations. Personal information was obtained by face-to-face interview. Information included the place of residence, age, sex, income, type of medical insurance, education level, body mass index, habits of smoking and drinking, type of work, working posture, duration of the same working posture during the day, mode of transportation, exposure to vibration, and daily amount of sleep. Crude and adjusted prevalence was calculated. The features of populations were analyzed by multivariable logistic regression in total and subgroup populations.
The study included 3859 adults. The crude and adjusted prevalence of lumbar osteoarthritis was 9.02% and 8.90%, respectively. There was no significant difference in the prevalence of lumbar osteoarthritis between urban, suburban, and rural populations (7.66%, 9.97%, and 9.44%) (P = 0.100). The prevalence of lumbar osteoarthritis was higher in females (10.05%) than in males (9.1%, P = 0.021). The prevalence of lumbar osteoarthritis increased with increasing age. Obese people (body mass index >28 kg/m), those engaged in physical work, those who maintained the same work posture for 1 to 1.9 hours per day, those who were exposed to vibration during daily work, and those who got less than 7 hours of sleep per day had a higher prevalence. These features differed by subgroup.
This study established epidemiological baseline data for degenerative lumbar osteoarthritis in adults, especially for people younger than 45 years. Lumbar osteoarthritis is epidemic in Beijing and will become a more severe problem in aging society. Different populations have different features that require targeted interventions.